Jobs in United States

Staff Engineer Code Generation in United States

1,760 active opportunities · Updated October 2026

Explore current staff engineer code generation jobs across United States. Filter by work mode, employment type, experience, department, date posted and distance.

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📍 New York, New York, United States· Full-time
✓ High-confidence listingCompany trend -84.7%

From $244K/yr

Quick readStrong listing-quality and freshness signals

As a Forward Deployed Engineer on the Feature Flags team, you'll partner directly with customers to accelerate their feature flag implementations — from initial architecture consulting through prototype builds to full-scale migrations. This role is for someone who wants to write code with customers, not just advise them. You'll work hands-on inside customer codebases to unblock complex, high-stakes deployments, directly influencing deal velocity and customer success. Working closely with Sales, Solutions, and Engineering, you'll be the technical force that turns a signed contract into a live, adopted implementation. What You'll Do: Serve as the hands-on technical partner for strategic customers implementing Datadog Feature Flags, from pre-sales technical validation through post-sales delivery Consult on flag architecture and implementation approach for complex environments — multi-service, multi-platform, high-scale deployments Build prototype flag implementations directly in customer codebases to prove value and de-risk technical decisions early in the sales cycle Implement flags across diverse and advanced deployment modes (server-side, client-side, edge, mobile, streaming/real-time) tailored to each customer's stack Drive full flag migrations to completion — including legacy system cutover — efficiently and with minimal customer engineering burden Identify patterns across customer implementations and feed them back to Product and Engineering to improve the core product and reduce future implementation time Collaborate closely with Engineering on technical edge cases, product gaps, and implementation tooling Partner with Sales and Solutions to accelerate deal cycles by removing technical risk and uncertainty Who You Are: 5 years of professional software engineering experience, with hands-on coding ability across the stack you're deployed into Experience with feature flagging, experimentation, or config management systems (internal or vendor) Comfortable dropping i

AIRustSEMHR
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📍 Nyc, New York, United States· Full-time
✓ High-confidence listingCompany trend -90.9%

$200K – $259K/yr

Quick readStrong listing-quality and freshness signals

We built Bubble with a clear mission: to empower everyone to create software. Our AI visual development platform lets anyone, from first-time entrepreneurs to enterprise teams, take an idea from prompt to fully-functional, scalable app across web, iOS, and Android. With over 6 million users in more than 100 countries, Bubble is breaking down the barriers to entrepreneurship and innovation worldwide. Our Product Bubble is the only fully visual AI app builder that lets you vibe code without the code to go beyond prototypes and launch real apps to real users. Chat with AI when you want speed, edit directly when you want control. Bubble's visual editor lets you fine-tune any detail, from the design to privacy rules and programming logic, so you're never stuck, even if AI hits its limits. Everything you need comes built in: a unified web and native mobile editor, enterprise-grade hosting, security, database management, and automatic scaling that grows with your business. You can build just about anything on Bubble, and our community is living proof. Mailead grew a $10K investment into a $2M valuation, and Faceless.video went from zero to $1M+ ARR in under a year. People aren't just launching products on Bubble, they're building real businesses. See how Bubble builders are shipping apps that change industries, solve problems, and shape the future here: Inspiring builders, breakthrough apps . Why Join Bubble Now? The rise of AI-generated software has validated everything Bubble has been building toward for over a decade. But pure AI-generated code is fragile, hard to debug, and rarely production-ready. Bubble bridges that gap, combining the speed of AI with a structured visual platform that produces stable, scalable, secure software. The people who join Bubble right now will help define what that means for millions of builders around the world. If you've ever wanted to work on something that genuinely changes who gets to build, this is your moment. About the Team: Mobile i

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📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.2%

About the Team The Infrastructure Engineering function sits within IT and is responsible for reliably building, deploying, and operating critical on prem and hybrid environments that power internal services and critical R&D environments. This is an early, high-leverage technical role focused on applying strong Site Reliability Engineering discipline to environments where uptime, safety, recoverability, and security are non-negotiable. This person helps replace bespoke, one-off infrastructure with standardized infrastructure-as-code building blocks that compound reliability and operational leverage as OpenAI scales. About the Role We are looking for an experienced Site Reliability Engineer working on security infrastructure to design, build, and operate reliable, secure, and scalable infrastructure that underpins identity, access, endpoint, and shared platform services across the company. In this role, you will be a senior technical owner for infrastructure and identity systems end to end, from architecture and implementation through policy enforcement, upgrades, recovery, and day-two operations. You will build durable, production-grade platforms that remove operational friction, enforce security by default, and enable teams to move faster with confidence. This role is well suited for a hands-on senior engineer who thrives in ambiguity, enjoys owning complex systems end to end, and raises the reliability and security bar by replacing fragile implementations with standardized, repeatable infrastructure. This role is based in our San Francisco HQ and requires in-office presence. In this role, you will: Design, build, and operate reliable infrastructure across on-prem, hybrid, shared, and product adjacent environments. Establish standardized infrastructure patterns that replace bespoke implementations with repeatable, auditable, secure-by-default systems. Own the lifecycle of critical infrastructure platforms, including provisioning, deployment, upgrades, patching,

AWSAzureRestAgile
Z
📍 Bellevue, Washington, United States
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

Zscaler (NASDAQ: ZS) accelerates digital transformation so customers can be more agile, efficient, resilient, and secure. The Zscaler Zero Trust Exchange™️ platform protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. Distributed across 160+ public exchanges globally and thousands of private exchanges at the edge, the SASE-based Zero Trust Exchange is the world’s largest in-line cloud security platform. We believe the future of work is Human + AI and are building an AI-native enterprise where human potential is amplified by machine intelligence to solve the world’s hardest security challenges. Driven by deep customer obsession, we are committed to the mission, outcome, and to each other. We bring these commitments to life through three core behaviors: ownership and collaboration, trust through outcomes and impact, and a challenge culture with ongoing feedback. Ready to make an impact at the company pioneering security transformation in the AI era? Join us at Zscaler. Role We are looking for a Staff Site Reliability Engineer (Production Engineer) to join our team. This is a hybrid role (onsite three days a week in San Jose, CA or another Zscaler office; remote can be considered for exceptional candidates) reporting to the Senior Manager, Site Reliability Engineering in the Zero Trust Exchange department. As a key member of the Zero Trust Exchange team, you will own the systems-level reliability and performance of Zscaler’s high-throughput bare-metal and cloud infrastructure processing tens of billions of daily transactions across a global, multi-region fleet. This is a software-first SRE role: you will write production-grade code and automation, drive the shift from reactive incident response, and bring engineering discipline to the systems-level work - OS, network and application debugging - that keeps the fleet operating safely at scale. What You’ll Do (Role Expectations) Maintain h

PythonKubernetesLinuxAI
T
📍 Seattle, Washington, United States
✓ High-confidence listing

$200K – $260K/yr

Quick readStrong listing-quality and freshness signals

The Forward Deployed Engineer, Staff (FDE) is a high impact technical leader responsible for translating the immense power of Talkdesk's Agentic AI platform into transformative, production grade solutions for our strategic enterprise customers. You are a unique blend of a highly experienced software engineer, a technical project lead, and a hands-on builder. You own the technical execution for deployments, mitigate technical risks, and drive successful customer outcomes across assigned projects. This role is for the experienced builder who excels in high stakes, customer facing environments and is passionate about defining the future of Customer Experience Automation. Responsibilities Technical Project Leadership & Architecture: Act as the technical lead for complex deployments. Design and implement the architectural blueprint for AI agent solutions, manage cross-system dependencies, and ensure designs meet stringent enterprise standards for security and scale. Hands-On Engineering & Delivery: Write production-grade code and leverage Talkdesk and 3rd-party APIs/SDKs to design, build, test, and deploy AI agents. Drive the execution from prototype through to production deployment, ensuring technical quality. Technical Consultation & Alignment: Serve as a trusted technical expert for our AI solutions. Confidently address deep technical inquiries, mitigate technical risk, and build trust with customer Engineering Directors, and technical architects. Influence Product & Engineering Roadmap: Synthesize and codify deployment learnings into reusable solution patterns and tooling. Provide actionable feedback to core Product and Engineering teams to help inform future product direction. Technical Guidance: Mentor junior FDEs and technical specialists on best practices for complex AI architecture, production quality, and client-facing technical delivery. Who You Are We are looking for an autonomous, results-driven technical leader who thrives at the intersectio

JavaScriptTypeScriptPythonAI
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📍 Austin, Texas, United States· Full-time
✓ High-confidence listing

$100K – $500K/yr

Quick readStrong listing-quality and freshness signals

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. We’re looking for a Staff Forward Deployed Engineer who’s excited to build with the engineers using the AI computers Tenstorrent makes. You will create continuity between customers, engineering, and AI inference service products. This is an engineering role first: you contribute production code, operate deployments, and you can explain a trade-off to customer leadership as clearly as to core engineering teams. This is a high-autonomy role with direct customer impact. This role is remote, based out of North America, with preference near one of our main hubs: Santa Clara, CA; Austin, TX; or Toronto, ON. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are You understand how accelerator compute, memory, and networking topology constrain AI workloads, and don't treat hardware as a black box. You're an early adopter of AI for your work from coding to building agentic workflows that multiply your impact. You work directly with customers to understand their challenges and provide effective solutions. You are comfortable debugging across the full inference stack: from failing requests, through the serving layer, down to OOMs or kernel dispatch if n

AWSKubernetesMachine LearningAI
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📍 San Francisco, California, United States· Full-time
✓ High-confidence listingCompany trend -72.4%

$155K – $400K/yr

Quick readStrong listing-quality and freshness signals

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role As a Staff Machine Learning Engineer on Sentry’s AI/ML team, you’ll be directly responsible for developing the models and agents used to make our product smarter and more capable. This role is crucial; you will be at the forefront of integrating AI and machine learning into our core products, from issue triage and resolution to predictive analytics for application performance monitoring. Your work will help companies around the globe gain actionable insights into their software, enabling them to build better products, faster. In this role you will Build state-of-the-art agentic AI systems to triage, debug, and solve real production issues Leverage Sentry’s novel (and massive) dataset of errors, spans, and profiles Own the development of major initiatives in the AI/ML space You'll love this job if you Are driven by impact and enjoy working on high-stakes, high-visibility projects Enjoy building things. You will have the opportunity to join the AI/ML team as one of its foundational members Thrive in cross-functional teams and enjoy building features alongside developers and product teams Qualifications Minimum 4+ years of professional experience with a MS/PhD degree in computer science, machine learning, or a related field Minimum 6+ years of professional experience with Bachelor’s degree in computer science, machine learning, or a related field Demonstrated expertise building production-grade agentic systems and tools You are comfortable writing production quality code (we use Python) Expertise with deep learning frameworks (we use PyTorch) Familiarity in deploying machine learning models at scale in production

PythonMachine LearningAIRust
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📍 New York, New York, United States· Full-time
✓ Quality checkedCompany trend -72.3%

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 Infrastructure team builds the platforms and tooling that help engineering teams develop, deploy, and operate production systems safely. Release Engineering owns the path from merge to production, including Plaid's zero-touch deployment system, progressive rollouts, metric-gated analysis, and automatic rollback. Our goal is to make safe shipping the default for every product team. As a Staff Site Reliability Engineer on Release Engineering, you'll define and scale Plaid's reliability practices across product engineering. You'll architect our SLO and error-budget programs, drive the adoption of progressive delivery, and ensure new products are production-ready. By partnering across product and platform teams, you'll translate complex production needs into intuitive, self-service tooling. This is a hands-on technical leadership role where you'll shape the future of our deployment systems—ensuring they remain fast and safe even as AI-assisted development increases code velocity. What excites you Lead the expansion of reliability standards across product engineering, converting foundational infrastructure into lasting operational habits and tooling. Architect and manage the SLO and error-budget

AWSKubernetesAIGo
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📍 United States· Full-time
✓ Quality checkedCompany trend -88.6%

At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. As a Staff Product Manager, AI Foundations at Vanta, you will build the core AI capabilities that power Vanta’s AI product experiences: the agent harness our agents are built on, and the quality and evaluation stack that makes them trustworthy. The AI pillar is making Vanta the intelligence layer for security and compliance work, wherever that work starts. We build the AI products and foundations that work across Vanta: a cohesive first-party Vanta Agent experience, headless surfaces like MCP and CLI that bring Vanta into tools like Claude Code and Codex, and the shared capabilities that let every team ship high-trust AI products. This role sits behind Vanta’s customer-facing AI experiences. Today, every team shipping AI features has to answer the same hard questions on their own: how to define quality, how to evaluate it, and how to know a change is safe to ship. You will turn those answers into shared foundations, so the AI experiences our customers rely on get better and more trustworthy over time. What you’ll do as a Staff Product Manager, AI Foundations at Vanta: Own the strategy and roadmap for Vanta’s core AI capabilities: the agent harness and the AI quality and evaluation stack Live in agent traces to build intuition for how customers actually use our AI products, and turn that into the highest-leverage improvements Make Vanta’s AI products win on quality: build golden datasets, automated evaluators aligned to expert judgment, and self-serve tooling so PMs, subject-matter experts, and designers can run evals without an engineer in the loop Scale the agent harness: shape the core capabilities Vanta’s agents are built on

RestAIGoRust
A
📍 United States
✓ High-confidence listingCompany trend +365.2%
Quick readStrong listing-quality and freshness signals

Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 122,000 colleagues serve people in more than 160 countries. JOB DESCRIPTION: Position Overview The Principal Data Engineer (IC) is a senior individual contributor and the accountable technical leader for assigned cross-domain initiatives and enterprise data engineering capabilities. The role owns integrated technical direction and technical outcomes for work spanning multiple data domains, defines and stewards enterprise engineering standards and reference architectures, and drives convergence where duplicated or inconsistent solutions create enterprise cost, risk, or operational burden. The role advises on scope, sequencing, capacity, dependencies, and technical debt, but does not independently commit domain resources or business delivery dates. This position has no people-management responsibility. Enterprise Data operates a domain-aligned model built on Databricks and Unity Catalog. Working with Domain Leaders, Staff Engineers, Platform Engineering, and partner organizations, the role converts ambiguous enterprise needs into executable architecture and carries the most complex or highest-risk work through validation and production. The role remains hands-on through prototyping, reference implementations, critical-path development, design and code review, and production problem solving. This role is based in Madison, WI. Essential Duties Include, but are not limited to, the following: Cross-domain technical leadership and delivery Own the technical outcome of assigned cross-domain initiatives from initial ambigu

PythonSQLAWSAzure
D
📍 New York, New York, United States· Full-time
✓ High-confidence listingCompany trend -84.7%

From $276K/yr

Quick readStrong listing-quality and freshness signals

Team description At Datadog, AI agents are becoming first-class consumers of observability, security, and software delivery data — from third-party coding agents like Claude Code, Cursor, and Copilot, to our own Bits SRE, Bits Assistant, and Bits Dev Agent. The Agentic Interfaces team owns the platform that connects these agents to Datadog: the MCP Server, the tools and retrieval surfaces agents call into, and — critically — the evaluation systems that tell us whether an agent's experience on Datadog data is actually getting better over time. This role is about that last piece. We're hiring a Staff Applied Scientist to define what "good" means for an Agentic interface at Datadog and to build the measurement systems that make it true. "Good" isn't one number — it spans answer quality, tool-selection accuracy, retrieval relevance, latency, token cost, and end-to-end agent success on real customer workflows. You'll design the evals, build the datasets, define the metrics, and partner with the AI engineers on the team to land the platform that lets every product group at Datadog ship integrations that are demonstrably better release over release. The space is full of open research questions. How do you evaluate an agent end-to-end when the trajectory is non-deterministic? How do you score tool selection when the tool catalog has hundreds of entries and grows weekly? How do you build a measurement system that catches regressions across first-party and third-party agents at once, without each team writing their own harness? If those are the problems you want to spend your time on, come build this with us. Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply. What You’ll Do: Own the evaluation strategy for Datadog's AI agent integrations. Define the metrics — offline and online, quali

AIGoRustSpring
D
📍 New York, New York, United States· Full-time
✓ High-confidence listingCompany trend -84.7%

From $204K/yr

Quick readStrong listing-quality and freshness signals

We’re looking for a Staff Product Designer to join the APM (Application Performance Monitoring) team. This team is focused on helping engineers agentically troubleshoot and optimize their applications. You'll learn the domain and proactively spot areas for improvement, getting stakeholder buy-in as needed. You'll own your design work end-to-end while helping shape broader product direction. You'll also hold a high bar for quality across the team and help other designers build support for their decisions. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Become a design leader within APM by proactively identifying opportunities and shaping the design strategy across multiple product areas and workflows. Partner closely with PMs and Engineers to ship intuitive experiences, balancing user needs with platform scalability and engineering constraints. Conduct and synthesize qualitative and quantitative research to identify pain points, validate solutions, and guide roadmap decisions. Communicate design rationale clearly and persuasively across design, engineering, product, and executive stakeholders. Mentor and support other designers by providing feedback, sharing frameworks and workflows, and helping raise the overall design quality bar across the organization. Prototype in code to rapidly explore ideas and validate concepts. Contribute to production code using AI-assisted workflows to ensure execution matches design intent. Help the team adopt AI-enabled design workflows. Who You Are: You have 10+ years of experience in digital product design. Your portfolio demonstrates a strong track record of designing and shipping complex technical products. You use AI-assisted workflows to prototype and rapidly iterate. You have a track record of connecting

GitRestAIGo
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📍 New York, new york, United States· Full-time
✓ Quality checkedCompany trend -67.9%

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for strong engineers with experience in making ML systems performant at scale. If you are interested in contributing to open-source projects and Modal’s container runtime to push language and diffusion models towards higher throughput and lower latency, we’d love to hear from you! Requirements: 5+ years of experience writing high-quality, high-performance code. Experience working with torch, high-level ML frameworks, and inference engines (vLLM or TensorRT). Familiarity with Nvidia GPU architecture and CUDA. Experience with ML performance engineering (tell us a story about boosting GPU performance — debugging SM occupancy issues, rewriting an algorithm to be compute-bound, eliminating host overhead, etc). Nice-to-have: familiarity with low-level operating system foundations (Linux kernel, file systems, containers, etc).

LinuxRestAIGo
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📍 United States· Full-time
✓ Quality checkedCompany trend -100%

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 This role is an exciting opportunity to be instrumental in creating magical collaboration workflows within ClickUp. Your focus will be on enabling teams and organizations to work together more effectively, fostering clear communication, coordination, and improved productivity. In this role, you'll have the opportunity to shape the collaboration experience in our products. Responsibilities: Uses AI to gather customer research, generate surveys and tests, and turn insight into clear UX. Prototypes flows, interactions, and logic using Claude Code, Cursor, for rapid iteration with customers and internal stakeholder alignment. Creates high-fidelity UI prototypes that push aesthetics, animation, and visual quality beyond what manual craft alone allows. Automates handoffs to engineering via Figma or vibecoded prototypes built with Claude Code or Cursor. Conduct user research to gain deep insights into user behaviors, pain points, and needs in the collaboration space. Collaborate with cross-functional teams, including product managers, engineers, and researchers, to define product strategy and roadmap for the collaboration experience. Create wireframes, prototypes, and high-fidelity designs that effectively communicate design concepts and interaction models. Conduct usability testing and gather feedback from users to iterate and improve designs. Work closely with front-end developers to ensure the design vision is implemented to the highest standard. Requirements: Minimum of 7 years of experience in product design, with a focus on collaboration or communication products. Strong portfolio demonstrating a track

AWSMachine LearningAI
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