Explore remote entry-level jobs worldwide

Deine Karriere Wir suchen einen erfahrenen, flexiblen Senior Software Architect – idealerweise mit Full-Stack-Hintergrund – der uns bei der Konzeption und Architektur komplexer Business-Anwendungen unterstützt und sich sicher in Cloud-Umgebungen wie AWS und/oder Azure bewegt. Bei nerdware steht nicht nur der Code im Mittelpunkt, sondern vor allem der Mensch dahinter. Die beste technische Lösung entsteht dort, wo Teamgeist, offene Kommunikation und gegenseitiges Vertrauen gelebt werden. Wenn du menschlich zu uns passt, hast du den wichtigsten Schritt bereits gemacht. Wir arbeiten in einer dynamischen und sich ständig verändernden Welt. Deshalb suchen wir Menschen, die Verantwortung übernehmen, neugierig bleiben und sich schnell auf neue Situationen einstellen können. Eigeninitiative, technischer Weitblick und die Freude daran, gemeinsam Lösungen zu entwickeln, sind uns dabei genauso wichtig wie ein respektvoller und wertschätzender Umgang im Team. Deine Aufgaben Konzeption und Architektur moderner Softwarelösungen – von der Anforderungsanalyse über Architekturentscheidungen bis zur produktiven Umsetzung Verantwortung für skalierbare, wartbare und performante Systemdesigns auf Basis moderner Technologien und Cloud-Plattformen Mitarbeit in spannenden Kundenprojekten als technische:r Ansprechpartner:in für Architekturfragen Identifikation und architektonische Einbindung von KI-gestützten Features oder Use Cases, wo sie fachlich sinnvoll und wirtschaftlich tragfähig sind Konzeption der Integration von Machine-Learning-Modellen, LLMs oder datengetriebenen Services in bestehende oder neue Systeme – abhängig vom Projektkontext Technologische Beratung unserer Kunden bei Architektur- und Technologieentscheidungen Sicherstellung von Code-Qualität und Architekturstandards durch Clean Code, Tests, Reviews und Best Practices Aktive Mitgestaltung neuer technologischer Themenfelder – insbesondere im wachsenden Bereich Künstliche Intelligenz Dein Profil Mehrjährige Erfahrung in der modernen Softwareentwicklung mit ausgeprägtem Architektur-Schwerpunkt, idealerweise im Fullstack-Umfeld Fundierte praktische Erfahrung im Bereich Künstliche Intelligenz (KI/ML) Erfahrung mit LLMs, generativer KI und datengetriebenen Systemen, inklusive Cloud-Architektur mit AWS und/oder Azure Selbstständige und verantwortungsbewusste Arbeitsweise mit stark ausgeprägten analytischen und konzeptionellen Fähigkeiten Fähigkeit, pragmatische Architekturlösungen für komplexe Anforderungen zu entwickeln und über den Tellerrand hinaus zu denken Sicherer Umgang mit Clean Code, SOLID-Prinzipien und der Gestaltung sauberer Softwarearchitekturen Hohe Motivation und Leidenschaft für Softwarearchitektur und -entwicklung Eigenverantwortliche, strukturierte Arbeitsweise und Begeisterung, neue Technologien aktiv voranzutreiben Sehr gute Deutschkenntnisse (C1) in Wort und Schrift Nice to have: Da wir als Dienstleister mit unterschiedlichen Kunden und Projekten arbeiten, freuen wir uns über Erfahrung in einem oder mehreren der folgenden Bereiche: Frameworks Angular .NET NestJS Programmiersprachen C# TypeScript Python Infrastruktur & Cloud Infrastructure as Code mit Terraform und/oder CDK Du musst nicht alles davon mitbringen – wichtiger ist uns deine Senior-Erfahrung, deine Lernbereitschaft und deine Fähigkeit, dich schnell in neue Technologien und Projektumgebungen einzuarbeiten. Was bieten wir Dir? Einige unserer Benefits: Tech, Ownership & Impact Architektur mitgestalten: Du triffst technische Entscheidungen, setzt Engineering-Standards und übernimmst Verantwortung für langlebige Systemdesigns. Makers Lab: Neben Kundenprojekten entwickelst du interne Tools und Lösungen, die uns wirklich weiterbringen. Wenn eine Idee gut ist, setzten wir sie um. Wissen teilen : In Show-How-Sessions und Workshops steuert jeder was bei – egal ob Junior oder Senior. Gezielte Weiterbildungen kommen obendrauf. Echtes Mitspracherecht: Flache Hierarchien bedeuten bei uns echte Entscheidungsfreiheit statt M

The Collections Analyst will assist in managing day-to-day collections operations for firm partners and will establish and maintain a system of monitoring and encouraging cash receipts.

About the Company:Talent Insider is an upcoming HR Consultancy Service, founded in 2021.

Are you a Georgian language expert eager to shape the future of AI?

Hey Future Daybreak Clinicians! At Daybreak Health, we’re building a world where every young person has access to the mental health support they need to thrive.

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview The Advertiser Optimization team is the decision-making engine of Instacart's $1B+ ads business. We own the systems responsible for Bidding, Pacing, Budgeting, and Targeting: converting stated advertiser goals into real-time auction actions. Our mission is to maximize realized Advertiser Value by deciding when to participate, how much to bid, and how fast to spend, all while balancing User Experience and Platform Revenue. We are hiring a Senior Applied Scientist II to lead the algorithmic direction of these systems. This is a role for someone who thinks in terms of control theory, constrained optimization, and auction economics, and who can translate those frameworks into production code that makes millions of decisions per day. You will formulate problems from first principles, shape the technical roadmap, and own systems end-to-end from mathematical design through production deployment through impact measurement. About the Job Design and evolve real-time bid optimization systems that translate advertiser goals (target ROAS, budget constraints) into optimal auction bids under uncertainty. Formulate the bidding problem as constrained optimization and build the feedback mechanisms that keep bids aligned with realized outcomes. Build intelligent budget pacing algorithms that distribute spend across time and auction opportunities. The core challenge: allocating a finite daily budget across stochastic demand while maximizing total value, subject to advertiser constraints and time-varying conversion dynamics. Develop the analytical frameworks that connect bidding, pacing, and budgeting into a coherent optimization objective. Shape auction mechanics including reserve pricing, multi-slot allocation, and bid-to-price mapping. Reason about mechanism design tradeoffs between advertiser outcomes, platform revenue, and marketplace efficiency. Own the full research-to-production loop: diagnose system behavior from large-scale data, formulate hypotheses, design experiments, ship production code, and measure impact. Write technical strategy documents that set the algorithmic direction for the team. About You Minimum Qualifications Graduate degree (Masters or PhD) in operations research, applied mathematics, control systems, computational economics, or a related quantitative field. 8+ years of experience building and deploying optimization or control systems in production environments (not just research prototypes). Strong foundation in at least two of: feedback control theory (PID, MPC), convex and stochastic optimization, auction theory and mechanism design, dynamic programming. Proficiency in one of the following languages: Go, Java, C++ for production systems and Python for data analysis and offline pipelines. Demonstrated ability to translate mathematical formulations into production code that runs at scale (millions of decisio

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview: We are looking for a Senior Machine Learning Engineer with a strong Operations Research background to join the Service Availability & Routing team within Instacart's Logistics organization. In this role, you will work at the intersection of combinatorial optimization, mathematical programming, and AI to solve high-impact problems in the fulfillment space — including order batching, shopper routing, service availability prediction, and real-time assignment. You'll partner closely with engineering, product, and data science to ship models and algorithms that directly influence Instacart's profitability and shopper experience at scale. The Logistics & ML group is responsible for the intelligence and execution behind Instacart’s fulfillment system. The team optimizes a multi-sided marketplace to ensure customers get their orders on-time and in high quality, shoppers get efficient and fulfilling work, and retailers and consumer brands get reasonable business. The team tackles hard problems in a variety of spaces, such as matching, pricing, and geospatial, as well as foundational problems executing on a high throughput system with dynamic data. About the Job: Design, develop, and deploy machine learning solutions to tackle practical challenges in the marketplace. Collaborate closely with product managers, data scientists, and backend engineers to deeply understand business needs and create impactful ML applications. Actively engage with diverse stakeholders to ensure that solutions are well-integrated and aligned with business goals. Push the envelope on our operational efficiency by continually refining and advancing our algorithms and models. About You: Minimum Qualifications: 3+ years of industry experience using machine learning to solve real-world problems with large datasets Have strong programming skills in Python and fluency in data manipulation (SQL, Pandas) and Machine Learning (scikit-learn, XGBoost, Keras/Tensorflow) tools Have strong analytical skills and problem-solving ability Are a strong communicator who can collaborate with diverse stakeholders across all levels Graduate degree (masters or PhD) in Operations Research or Industrial Engineering or closely related field Preferred Qualifications: Knowledge of deep learning frameworks and methodologies Experience in applying machine learning and optimization techniques to solve marketplace problems #LI-Remote Instacart provides highly market-competitive compensation and benefits in each location where our employees work. This role is remote and the base pay range for a successful candidate is dependent on their permanent work location. Please review our Flex First remote work policy here . Offers may vary based on many factors, such as candidate experience and skills required for the role. Additionally, this role is eligible for a new hire equity grant as wel

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview As a Senior Machine Learning Engineer II on the Ads Response Prediction team, you will lead the design and development of core ML models that power Instacart’s ads ecosystem. This is a research-leaning role focused on theoretical problem formulation, training methodology, and model quality rather than infrastructure or full-stack engineering. You will tackle fundamental challenges in pCTR modeling such as mitigating selection bias, position bias, and optimizer’s curse in training data, improving model calibration across surfaces and domains, and advancing our multi-task learning and sequence modeling capabilities. You will also have the opportunity to shape our next-generation foundation model approach for ads ranking and contribute to cutting-edge retrieval systems like TIGER (Transformer Index for Generative Recommenders), Semantic ID and domain language models. The Ads Response Prediction team owns all systems, algorithms and ML models to ensure a relevant and engaging Ads experience to customers of all the platforms powered by Instacart. This includes search and exploration retrieval systems, sequential modeling and generative retrieval systems for next interaction recommendations, LLM integrations, relevance models, pCTR models, bidding models and incrementality models. The team optimizes for an efficient marketplace to ensure delightful customer shopping experience, desirable advertiser business outcome and Instacart Ads revenue. The team has strong ML infrastructure and MLOps support, including Delta/DBT-Spark data pipelines, Ray-based distributed training, and automated model deployment. This means you can focus your energy on advancing modeling science rather than building infrastructure. About the Job Lead research and development of pCTR and conversion prediction models, with a focus on improving calibration, reducing training data biases (selection bias, position bias, optimizer’s curse), and advancing model accuracy across Instacart’s ads surfaces. Design and implement debiasing techniques such as Mixed Negative Sampling (MNS), Inverse Propensity Weighting (IPW), counterfactual risk minimization, and calibration methods (Platt scaling, isotonic regression) to address systematic prediction biases. Contribute to the next-generation Multi-Domain Multi-Task (MDMT) model architecture, incorporating innovations like Mixture-of-Experts (MoE), Transformer layers for sequential user behavior, and LoRA adaptors for scalable domain fine-tuning. Drive sequence modeling initiatives including the TIGER generative retrieval system and Semantic ID representation learning, expanding their application across ads surfaces such as Product Details, Search and other placements. Collaborate with the broader ML community in the company on the path toward Foundation Models using autoregressive user behavior prediction. Formulate

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview The Search & Personalization ML team is Instacart’s engine for state-of-the-art multi-task, multi-objective ranking—unifying search, discovery, recommendation, ads, and merchandising into a single value-aware platform. Partnering with world-class engineers, scientists, and PMs, we build the ranking backbone that powers every pixel of the shopping journey, optimizing not just for clicks, but for incremental GTV, basket lift, and retention over the long run. What We’re Building Foundational Ranking Backbone Models: Multi-task/multi-objective models (shared encoders + task heads) that jointly learn relevance, conversion, margin contribution, churn risk, and ad quality, enabling consistent decisions across search and recommendations. Value-Aware Optimization: Uplift and long-horizon value models that steer decisions toward incrementality and LTV, with calibrated constraints on quality, diversity, fairness, and spend pacing—plus guardrails for safe exploration. LLM-Enhanced Retrieval & Features: Using LLMs to enrich query and item semantics for long-tail recall, generate features for cold-starts, and feed the ranker with reasoning-rich context, while remaining the source of truth for final ordering. Our commitment to AI innovation is reflected in our recent publications and research contributions to the field. About the Job Architect the ranking backbone that unifies query understanding, personalization, multi-objective ranking, ads, and merchandising into a single adaptive platform. Design and build a search autosuggest system optimized for personalization and value-based relevance. Design long-horizon objective functions (e.g., incrementality, LTV, habit formation) and build uplift/causal value models that move beyond short-term engagement. Develop production-grade Multi-Task Learning (e.g., shared encoders, MMOE/PLE task heads) to jointly learn relevance, propensity, margin, and churn risk—ensuring calibration, constraints, and explainability. Own the inference layer: goal-aware re-rankers, diversity and quality constraints, safe exploration, and millisecond-class latency optimization. Advance evaluation practices: online experiments, long-horizon cohort metrics, counterfactual evaluations, and attribution pipelines for tracking incremental GTV and retention. Partner across ads, infrastructure, product, and design teams to translate business goals into ranking policies and measurable ROI. Mentor ML engineers to build expertise in ranking, causal inference, and scalable serving systems. About You Minimum Qualifications 4+ years applying ML at scale with a Master’s degree, or 2+ years for PhD, with a proven track record improving ranking or recommendation systems in production. Demonstrated success in applying multi-objective or constrained optimization to balance relevance, revenue, margin, and user experience; experien

About the Role and Team This internship sits at the commercial heart of Uber Eats. You'll join an Account Management team and take on real ownership of partner performance across a portfolio of restaurant brands. Account Management at Uber Eats is fundamentally a commercial function. Your job is to grow revenue for partners and for Uber. That means you'll be working with data daily, running business reviews, identifying where performance is lagging and why, and translating that analysis into concrete recommendations that move the needle. This isn't an observational role. From week one, you'll carry a workstream, supper the team with a set of accounts, and be expected to show up to conversations with a point of view grounded in data. This internship offers hands-on exposure to commercial operations, account management, customer success, and cross-functional project management in a fast-paced environment. What You'll Do Commercial Performance & Partner Growth Support the AM team across a set of accounts, tracking performance against commercial KPIs: GMV, order volume, conversion rate, basket size, and customer retention. Work with the AM Team to support restaurant partners to identify growth opportunities and recommend commercial solutions. Support outbound partner conversations with clear commercial objectives. Support the sale of Ads & Offers products by articulating their value and helping partners adopt them. Run structured business reviews: prepare the analysis, identify the growth levers, and land a clear recommendation. Build the narrative behind the numbers translating data into a story that drives partner action. Support expansion conversations: new site launches, geographic growth, and cross-sell opportunities within existing accounts. Data Analysis & Insight Generation Run structured performance diagnostics: identify where a partner is underperforming versus benchmark and why. Build and maintain reporting dashboards that surface the metrics that matter. Develop and test hypotheses about what drives partner revenue then work with the team to act on them. SQL exposure is a plus but not required; comfort with Excel or Google Sheets and a structured analytical mindset is essential. Marketing Execution & Demand Generation Execute performance marketing campaigns promotions, visibility boosts, pricing experiments and rigorously track ROI. Identify where marketing investment will generate the highest incremental return for a given partner. Analyse post-campaign data to draw conclusions and feed learnings back into future strategy. Basic Qualifications Currently enrolled in a Bachelor's or Master's degree program (e.g., Business Administration, Economics, Marketing, Operations, Data Analytics, or related fields), with graduation by early 2027. Available for a full-time, 6-month internship starting 7th September 2026 Proficiency in Excel or Google Sheets, including data extraction and analysis Native in German and fluency in English Strong communication and stakeholder management skills Open to exploring full-time opportunities with Uber following the internship in case a role becomes available. Who Thrives Here The interns who get the most from this role arrive curious about the numbers, comfortable being challenged on their thinking, and genuinely interested in how commercial relationships work. They take ownership early, ask sharp questions, and know the difference between being busy and having impact. If that sounds like you, we'd like to meet you ~~ ~~ Ready to Ride? This isn't the kind of place where you follow a playbook - it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves - we'd love to hear from you. You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits. Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of the

The ideal candidate will be based in Germany and should be willing and able to travel across Europe for additional client engagements as needed. About Us: Pacvue is the leading Commerce Media OS, powering over $12B in advertising spend across 100+ global retail media networks including Amazon, Walmart, Target, Kroger, Instacart, Criteo, and CitrusAd. Powered by industry-leading AI and real-time data, Pacvue enables over 70,000 brands and agencies to maximize advertising performance, drive incrementality, and expand reach across the commerce universe from a single mission control. As of 2025, Pacvue powers 12% of total retail media ad spend worldwide excluding China. Combined with Helium 10’s SMB solutions, Pacvue delivers the industry’s most comprehensive platform for businesses of all sizes. At Pacvue and Helium 10, great careers don’t just happen — they’re built. Here, you’ll rise as an industry leader, push the boundaries of innovation, own your journey, and thrive as part of an inclusive global community that’s redefining the future of commerce. About the Role: As an Account Manager, Enterprise Partnerships at Pacvue, you will support the day-to-day management of client accounts across a portfolio of European agency clients, primarily independent Amazon and ecommerce agencies, and ecommerce brands with growing exposure to enterprise-level retailers such as Amazon and other regional platforms. This role will involve working closely with internal team members and client stakeholders across multiple European markets to help execute partnership plans, ensuring clients achieve success through our platform while supporting overall revenue goals for Pacvue. You will be expected to leverage your analytical skills, communication abilities, and insights to assist with client outcomes and support ongoing account activities in a dynamic, fast-growing international environment, and using data to tell the story. Responsibilities: Client Relationship Management: Own the end-to-end success of assigned European client portfolio. Make independent decisions on strategy, performance management, and client communications with only critical decisions reviewed. Accountable for revenue growth, client retention, and regional market outcomes. Build and nurture partnerships that support client success and contribute to Pacvue’s regional revenue growth. Act as a supporting consultant to clients, offering guidance on eCommerce best practices, marketplace dynamics, and performance optimization across European platforms. Strategic Planning & Consultation: Analyze client data across multiple European marketplaces to uncover insights and opportunities for improvement, leveraging Pacvue's platform to recommend solutions aligned with client business objectives. Lead strategy sessions with clients, independently determining the approach to localized eCommerce strategies. Make autonomous decisions on optimization priorities, regional tactics, and resource allocation, with oversight only at critical milestones. Independently identify, evaluate, and execute upsell and cross-sell opportunities within assigned accounts by assessing client data, market conditions, and product fit. Devise solutions and strategies with minimal senior oversight. Cross-Functional Collaboration: Collaborate across Sales, Customer Success, Product, and Marketing teams as a strategic advisor on client needs and market opportunities. Influence team priorities based on regional market insights; may mentor junior team members on account strategy. Collaborate with senior team members to align client objectives with Pacvue’s product roadmap, incorporating regional market insights and needs. Performance & Reporting: Regularly track and report on client performance across European markets, providing analysis and actionable recommendations to drive improved results. Monitor key performance indicators (KPIs), using data insights to proactively suggest adjustments to strategies, channel mix, or re

About the Team People Innovation Labs is a fast-moving engineering team embedded in OpenAI’s People Team. We build the systems, products, and AI-native workflows that help OpenAI find, grow, support, and retain exceptional talent. We work across recruiting, HR, culture, knowledge, performance, and employee experience to rethink how the People Team should operate in the age of AI. Some of what we build are durable internal products; some begin as prototypes, automations, workflows, or experiments with the potential to become software products over time. About the Role We’re looking for a Product Manager focused on AI enablement, prototyping, and product discovery within the People Team. This person will act as a forward deployed PM for People Innovation Labs: embedded with OpenAI’s People Team, close to the work, and responsible for finding the highest-leverage opportunities where AI can meaningfully improve how OpenAI operates. You’ll partner with subject matter experts within the People Team to identify pain points, prototype new AI-powered workflows, help colleagues adopt emerging tools, and determine which ideas should remain lightweight enablement versus graduate into durable products built and maintained by PIL engineering. The role sits at the intersection of product, AI enablement, internal operations, and hands-on exploration. This is ideal for someone who is builder-minded, highly trusted by operators, comfortable in ambiguous problem spaces, and able to move fluidly from “let’s try this today” to “this should become a real product.” In this role, you will - Act as the product lead embedded within the People Team, helping identify, prototype, and scale high-impact AI use cases across recruiting, HR, culture, talent, and company-wide operations. - Partner closely with People Team subject matter experts to understand workflows in depth, uncover friction, and translate operational needs into AI-native solutions. - Build, test, or shape lightweight prototypes using OpenAI tools, internal systems, no-code/low-code workflows, agents, automations, or other fast experimentation methods. - Help the People Team adopt and use AI effectively, including developing patterns, playbooks, examples, and lightweight enablement materials. - Identify which prototypes, workflows, or repeated pain points should become durable software products owned by PIL engineering. - Translate successful explorations into clear product briefs, requirements, success criteria, and handoff plans for engineering and design. - Work with PIL engineers to evaluate technical feasibility, sequence investments, and make pragmatic tradeoffs between speed, quality, privacy, security, and maintainability. - Maintain a portfolio view of AI enablement opportunities within the People Team, distinguishing between experiments, one-off tools, scalable workflows, and product candidates. - Build trusted relationships with People Team leaders, operators, and technical partners, serving as connective tissue between frontline needs and product strategy. - Define success metrics for prototypes and launched products, including adoption, time saved, workflow quality, user satisfaction, and operational impact. - Bring learnings from People Team workflows back into PIL’s broader product roadmap and, where relevant, into OpenAI’s understanding of how AI changes knowledge work. You might thrive in this role if you - Have 5+ years of experience in product management, technical product strategy, founder/operator roles, AI enablement, solutions/product lead roles, or similar work that combines product judgment with hands-on execution. - Are energized by ambiguous, high-context environments where the right answer may start as a scrappy prototype before becoming a roadmap item. - Have strong product instincts and can tell the difference between a useful one-off workflow, a scalable internal pattern, and a product worth engineering investment. - Are hi