Ai Engineering Director in United States

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 Commercial Scaled Intelligence (CSI) team is an AI-first team dedicated to delivering actionable commercial insights and scalable automation to drive revenue growth and operational efficiency across the company. The team focuses on intelligence generation, predictive analytics, and workflow automation to enable data-driven decision-making and optimize commercial performance. As an Ads AI Analytics Lead II, you will own the intelligence behind our Ads agents. You will design the Ads semantic/context layer and build vertical AI agents that analyze campaigns, diagnose performance, and recommend actions that improve ROAS, pacing, and partner outcomes. You will partner with Ads GTM, Product, Data Science, and Engineering to ship production agents with measurable lift. About the Job Define Ads ontologies and metrics for campaigns, budgets, bids

About the team The Applied AI Engineer, Digital Natives team is responsible for ensuring the safe and effective deployment of Generative AI applications for developers and enterprises. We act as a trusted advisor and thought partner for our customers, working to build an effective backlog of frontier AI use cases for their industry and drive them to production through strong technical guidance. As an Applied AI Engineer in the Digital Native segment, you’ll help large and highly sophisticated companies transform their business through custom AI solutions applications such as customer service, automated content generation, contextual search, personalization, and other novel use cases leveraging OpenAI’s newest, most exciting models and latest capabilities. About the role We are looking for a driven solutions leader with a product mindset to partner with our customers and ensure they achieve tangible business value with frontier AI. You will pair with senior customer leaders to establish AI strategic roadmaps and identify the highest value applications. You’ll then partner with their engineering and product teams to move from prototype through production. You’ll take a holistic view of their needs and design an enterprise architecture using OpenAI APIs and other services to maximize customer value. You will collaborate closely with Sales, Solutions Engineering, Applied Research, and Product. This role is based in our NYC office. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Deeply embedded with our most sophisticated and technical platform customers, serving as their technical thought partner in ideating and building novel applications on our APIs. Proactively provide guidance to our customers on how to maximize business impact from their applications, accelerating their time to value. Experiment and prototype solutions with and for your customers. Forge and manage relationships wi

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role: We’re seeking an experienced UX Researcher to define and scale how we evaluate Notion’s AI-powered experiences—focusing on what “good” looks like not only for model output quality, but for the end-to-end product experience where people discover, set goals, delegate work, review results, and build trust over time with AI. This role sits at the intersection of research craft and evaluation operations: you’ll run studies that uncover user mental models, expectations, and failure/recovery behaviors, then translate those insights into reusable rubrics, workflows, and measurement approaches that product, design, engineering, and data science can apply consistently. This role can be based in either San Francisco or New York City. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. What You'll Achieve: Define what “good” looks like (frameworks & rubrics): Establish clear, reusable evaluation criteria that reflect real user expectations—helpfulness,

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. Our team builds AI-driven software systems for Circuit Design: combining automation algorithms, DL models and agentic workflows to accelerate end-to-end design automation. Come join this integral team in our Circuit Solutions Group! What you'll be doing: Work within a multi-functional team on various projects involving Pre-silicon and Post Silicon custom circuit design and related data, Circuit/Layout Optimization and Spice correlation Research and implement techniques on frontier solutions of electronic design automation. Build and innovate agentic AI solution for VLSI design problem. Responsible for analyzing the problem or datasets, raise and validate hypotheses, design and build models and algorithm until they reach the desired QOR. What we need to see: MS (or equivalent experience) with 3+ years’ experience or PhD with 1+ years’ experience in Electrical/Computer Engineering degree Experience in the following fields is a strict requirement for this role: Combinatorial Optimization, Agentic AI and large language models, Machine Learning for Chip Design & EDA Experience in Algorithms/Data Structures/

We are seeking an experienced Senior Generative AI Developer to help drive the design, development, and integration of state-of-the-art Generative AI and agentic AI solutions across our enterprise Controls Technology platform. You will collaborate with cross-functional teams, contribute deep technical expertise in context engineering, retrieval systems, knowledge graphs, and multi-agent orchestration, and play a key role in delivering scalable, grounded AI solutions to enhance automation and operational efficiency. This role centers on architecting robust applications and agent systems on top of pre-trained and hosted foundation models — not on training or fine-tuning models. Key Responsibilities Collaborate with AI architects, leads, and stakeholders to design and implement generative and agentic AI solutions that address business challenges. Architect advanced context engineering strategies — context layering, chaining, compression, pruning/offloading, and memory management — to maximize reliability, provenance, and token efficiency in production. Design and implement advanced generative AI methods, including sophisticated prompt engineering and Retrieval-Augmented Generation (RAG) . Build and optimize RAG systems , including hybrid search, multi-vector retrieval, and re-ranking pipelines. Design and implement knowledge graphs and Graph RAG architectures to enable multi-hop reasoning, explainability, and traceable, grounded responses for high-value business domains. Architect agentic workflows and multi-agent systems using Google Agent Development Kit (ADK) and comparable frameworks (LangGraph, Microsoft Agent Framework, CrewAI), applying orchestration patterns such as supervisor/worker, hierarchical, and peer-to-peer. Design robust agent harnesses — governance, constraints, feedback loops, state/session management, and

About the Team OpenAI develops models that can reason through complex problems and hardware designed for the demands of advanced AI. AI for Chips connects these efforts: applying increasingly capable AI systems to the work of semiconductor engineering. Our goal is to help engineers develop better chips and shorten design cycles. This work brings research, model training, and hardware expertise together to build tools that engineers can use on real designs, with correctness and measurable performance at the center. About the Role We’re hiring a Research Engineer to help OpenAI models solve chip-design problems through reinforcement learning, tool use, and evaluation. You’ll own experiments from the initial idea through implementation and analysis. That means building environments and evaluations, running training, investigating failures, and using the results to decide what to try next. You’ll also build the software needed to make those experiments reliable and reproducible. We value strong coding fundamentals, careful experimental judgment, and the ability to make progress independently. Prior chip-design experience is helpful, but you can learn the domain alongside the team’s hardware specialists. In this role, you will: Build RL environments and evaluations for tasks such as RTL generation, design verification, and physical design optimization. Develop and test approaches that help models use chip-design tools and improve power, performance, and area while preserving correctness. Design experiments, establish baselines, and measure whether improvements hold up on new tasks and designs. Investigate failures across model behavior, rewards, evaluation tools, and experiment infrastructure. Improve iteration speed through better tooling, faster evaluations, and proxy rewards that reflect the outcomes we care about. Turn successful experiments into reusable research code and training workflows, working closely with researchers and engineers. You might thrive in this ro

About the Team OpenAI develops models that can reason through complex problems and hardware designed for the demands of advanced AI. AI for Chips connects these efforts: applying increasingly capable AI systems to the work of semiconductor engineering. Our goal is to help engineers develop better chips and shorten design cycles. This work brings research, model training, and hardware expertise together to build tools that engineers can use on real designs, with correctness and measurable performance at the center. About the Role We’re hiring a Software Engineer to build the research infrastructure and tooling that help OpenAI models design silicon. You’ll turn chip-design workflows into reliable environments for reinforcement learning and evaluation, and make it easier for researchers to run experiments and iterate on new ideas. You’ll move between software engineering, tool integration, and open research problems. We value strong coding fundamentals, clear technical judgment, and independent execution. Prior chip-design experience is helpful, but you can learn the domain alongside the team’s hardware specialists. In this role, you will: Build and maintain infrastructure for reinforcement learning environments, evaluations, and long-running experiments. Integrate electronic design automation (EDA) tools into workflows for RTL generation, verification, and physical design optimization. Improve experiment reliability, reproducibility, observability, and performance; debug failures across tools, services, and infrastructure. Develop tooling and model harnesses that let researchers test ideas quickly and measure correctness and power, performance, and area (PPA). Collaborate with researchers and engineers to turn successful experiments into reusable systems and training workflows. Own ambiguous projects end to end, communicate progress, and use results to guide the next iteration. You might thrive in this role if you: Have strong software engineering fundamentals, with

Become a part of our caring community The Lead Software Engineer codes software applications based on business requirements. The Lead Software Engineer works on problems of diverse scope and complexity ranging from moderate to substantial. The Lead Software Engineer standardizes the quality assurance procedure for software. Oversees testing and debugging and develops fixes. Researches complaints and makes necessary adjustments and/or recommendations to resolve complex software related issues. Advises executives to develop functional strategies (often segment specific) on matters of significance. Exercises independent judgment and decision making on complex issues regarding job duties and related tasks, and works under minimal supervision, Uses independent judgment requiring analysis of variable factors and determining the best course of action. Key Responsibilities Technical Architecture and Ownership:** Design and own the end-to-end architecture of Centerwell's AI systems, including LLM-powered clinical tools, RAG pipelines, harnesses, agent-based workflows, and intelligent automation. Make and communicate foundational technical decisions in close collaboration with the broader engineering team. Model Development and Fine-Tuning:** Evaluate, select, and where appropriate guide the fine-tuning of foundation models. Establish model evaluation frameworks that prioritize safety, accuracy, and clinical relevance. Clinical and Product Partnership:** Collaborate closely with product managers, designers, clinicians, and data stakeholders to understand care delivery workflows and translate them into well-scoped, high-impact AI features. HIPAA Compliance and Responsible AI:** Ensure all AI systems are designed, deployed, and monitored in compliance with HIPAA and Humana's Responsible AI standards, including participation i

NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can address, and that matter to the world. This is our life’s work, to amplify human creativity and intelligence. Make the choice to join us today. Design-for-Test Engineering at NVIDIA works on groundbreaking innovations involving crafting creative solutions for DFT architecture, verification and post-silicon validation on some of the industry's most complex semiconductor chips. What you'll be doing: As a senior member in our team, you will work with pre-silicon and post-silicon data analytics - visualization, insights and modeling. Design and uphold sturdy data pipelines and ETL processes for the ingestion and processing of DFX Engineering data from various origins Lead engineering efforts by collaborating with cross-functional teams (execution, analytics, data science, product) to define data requirements and ensure data quality and consistency You will work on hard-to-solve problems in the Design For Test space which will involve application of algorithm design, using statistical tools to analyze and interpret complex datasets and explorations using Applied AI methods. In addition, you will help develop and deploy DFT methodologies for our next generation products using Gen AI solutions. You will also help mentor junior engineers on test designs and trade-offs including cost and quality. What we need to see: BSEE (or equivalent experience) with 5+, MSEE with 3+, or PhD wi

Data Architect, AI and Supply Chain Insights Description - Job Summary We are seeking a Supply Chain Data Architect who combines strong data architecture expertise with a data product mindset. The role is responsible for owning and evolving a portfolio of Data Products, designing scalable and reusable data models, and ensuring data assets are trusted, governed, and optimized for reporting, analytics, Data Science, Machine Learning, and AI use cases. The successful candidate will work closely with business stakeholders to understand processes, priorities, and opportunities, translating them into data strategies and architecture solutions that maximize business value and adoption. A strong understanding of data engineering concepts is foundational and required, including how data is acquired, transformed, and delivered across modern data platforms. The primary focus of the role is on data architecture, data modeling, data product maturity, business engagement, and AI ready design. Success is measured by the ability to create scalable, business ready data products that enable self service analytics, advanced insights, continuously leveraging the evolving AI technologies for our Supply Chain Stakeholder. The ideal candidate combines deep expertise in data architecture and modeling with business acumen, critical thinking, problem solving and a passion for innovation. They partner with business leaders, Data Engineers, Data Scientists, Product Owners, and AI practitioners to transform complex business challenges into data driven solutions Responsibilities Own and evolve a portfolio of Supply Chain Data Products, ensuring they are certified, compliant, governed, and aligned to the latest Data Governance standards while maximizing business value and adoption. Partner with busi

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role: Own how our Foundations business teams design, automate, and operate their most important workflows. Notion is growing quickly, and the processes that run our business — intake, triage, execution, approvals, escalations, reporting — need to scale without adding headcount or losing auditability. This role exists to redesign those processes end to end and to embed AI directly into them, so the work moves faster and the system stays trustworthy. What's different at Notion: you'll build on Notion as customer zero. You'll design multi-system workflows spanning Notion, Slack, email, support tooling, and internal data, then ship the custom agents, skills, and automations that run them — partnering with Finance, Legal, People, Ops, Data, and Engineering to drive real adoption, not just documentation. This role can be based in either San Francisco or New York City. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. What You'll Achieve: Redesign cross-f

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? We’re seeking an experienced Engineering Program Manager to join Cohere’s customer-facing Engineering Program Management team. We need someone with curiosity, drive, independence, and leadership, who has hands-on experience working directly with customers and managing projects for enterprise-grade software or enterprise-focused machine learning solutions. In return, you’ll have the unique opportunity to shape Cohere’s operations, collaborate with leading minds in the LLM space, work directly with our Strategic Customers as well as Applied ML (AML) Engineering, Forward Deployed Engineering (FDE), Platform , Product and Go-to-Market teams, and be the “technical” voice of Cohere for the customer. You will get a chance to create extremely high-impact contributions to our fast-growing company, product and culture. As an Engineering Program Manager/ Technical Program Manager, you will: Communicate: Provide clear, timely, and objective communication across the tech organization, Cohere teams, leadership, and most importantly - our strategic customers and external partners. Optimize: Break down complex issues into strateg

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE: Voice is becoming the internet’s next interface, but a production-grade Voice AI system is "hard to build" . You’ll join a small founding team of Baseten Voice AI, focused on bringing state-of-the-art open source models into production for Voice AI customers across productivity, customer service, clinical conversation, creator tools, education, and more. You’ll make a meaningful impact on people’s daily lives and help reshape these industries. This is a high-impact, high-ownership role. You will be the primary owner of Baseten Voice AI - our in-house inference stack to power Voice AI models - from product roadmap through engineering implementation. You’ll partner closely with Forward Deployed Engineers, Model Performance Engineers, and sister engineering teams to push the boundaries of Voice AI. EXAMPLE INITIATIVES: Develop world-class model serving stack for state-of-the-art open-source voice models - reduce end-to-end and tail latency (p95/p99), increase throughput, and improve GPU efficiency via profiling, runtime tuning, and server-level optimizations. Build large-scale, real-time infrastructure for multi-model voice agents - orchestrate STT, TTS, and agent components with streaming I/O to meet customer SLOs. Design tight training and inference iteration loops for voice model customization - enable fast evaluation, safe rollout, and rapid experimentation for custom voice model development. Past projects:

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. Plaid’s Product team builds the network that powers the future of financial services. Our mission is to unlock financial freedom for everyone through open finance. Product Managers at Plaid are curious, customer-obsessed, and move quickly to deliver value. They take ownership, sweat the details, and make sound decisions with imperfect information. As a Product Manager on the AI Foundations team, you will drive Plaid’s AI strategy by building the data and intelligence layer that powers smarter financial experiences. You will work across engineering, data science, and research to develop scalable AI systems—from core embeddings and representation learning to applied model integrations that enhance developer and consumer outcomes. This role is for an experienced PM who thrives at the intersection of AI and platform products. You are technically fluent, strategic, and execution-oriented. You enjoy turning advanced machine-learning capabilities into reliable, trusted infrastructure that scales across Plaid’s ecosystem. Responsibilities AI Platform Vision: Define the strategy, roadmap, and success metrics for Plaid’s core AI and data foundation, enabling smarter, more adaptive financial products across th

We are a global team of innovators and pioneers dedicated to shaping the future of observability. At New Relic, we build an intelligent platform that empowers companies to thrive in an AI-first world by giving them unparalleled insight into their complex systems. As we continue to expand our global footprint, we're looking for passionate people to join our mission. If you're ready to help the world's best companies optimize their digital applications, we invite you to explore a career with us! Your opportunity Every company shipping AI right now has the same problem: they can't see what their AI is actually doing in production. New Relic is building the answer, AI Observability, and it's one of the company's top strategic initiatives. We're running it like a startup inside the company: small teams, fast iteration, direct executive sponsorship, and a mandate to ship. As the Principal Product Manager and business owner of this initiative, you'll take it from vision through GA, then keep pushing past GA, where most of the real work actually happens, working directly with some of the largest AI deployments in the world. What you'll do Own the AI Observability roadmap and the business outcomes leadership tracks (adoption, retention, expansion), plus the parts of the job that aren't purely product: pricing conversations, exec reporting, and cross-functional escalations. Drive multiple engineering and design teams in parallel toward a coherent product vision, without formal authority over them. Partner directly with strategic enterprise customers, including their platform and infra teams deciding how to operationalize AI safely, and turn what breaks at their scale into product requirements fast enough to matter. Build working prototypes yourself using agentic AI workflows, so ideas get pressure-tested before engineering time is committed to them. Represent AI Observability in executive strategy and prioritization decisions, and make the tradeoff calls when prioritie