AI Engineer
Distyl AI
Listing collected from Distyl AI's career site. NextChapter is independent of Distyl AI.
San Francisco, CA · Posted June 18, 2026
Just laid off? Start here: a plan for the first weeks
See every open role at Distyl AI
More in California job market · All AI Engineer jobs (165) · Technology & Software · Data & Analytics jobs
More roles at Distyl AI
- AI Engineer (French Speaking)
- AI Engineer, Enterprise Lead · San Francisco, CA
- Lead AI Strategist · San Francisco, CA
- AI Strategist, Healthcare Solutions · San Francisco, CA
- AI Engineer, Lead · San Francisco, CA
- Applied AI Researcher, Multi-Agent Systems · San Francisco, CA
Similar jobs
- Principal AI Engineer, Sr AI Engineer · Baker Tilly · CA
- Senior AI Compute Engineer - NVIS · Nvidia · Santa Clara, CA
- Applied Machine Learning Engineer, AI for VLSI Design - New College Grad 2026 · Nvidia · Santa Clara, CA
- AI Tooling Software Engineer - Data Platform, Autonomy · Zipline · CA
- Senior Principal AI Solutions Engineer · SambaNova Systems · San Jose, CA
- Principal AI Platform Engineer [Hybrid] · EDF power solutions · San Diego, CA
Where San Francisco, CA ranks
Where San Francisco, CA placed in our monthly rankings, month by month. Each month stays online at its own address.
November 2026
- #1Best cities for security jobs316 openings · of 20
- #1Best cities for technology jobs7,178 openings · of 100
- #1Best cities for financial services pay after cost of living$173k · of 33
- #1Best cities for entry-level jobs that want AI skills35% · of 100
- #1Best cities for entry-level jobs that want AI skills in the West Coast35% · of 54
- #1Cities with the most jobs that do not need a four-year degree in the West Coast902 jobs · of 47
Rankings about data & analytics jobs
- Best cities for data and analytics jobs #1 New York (1,713 openings)
- Best cities for data and analytics pay after cost of living #1 Foster ($232k)
- Most requested AI skills in data and analytics jobs #1 Machine learning engineering (17.1%)
- AI tools named most often in data and analytics jobs #1 Databricks (7.6%)
- Employers with the most data and analytics jobs #1 Amazon (711 roles)
Data & Analytics jobs · Top Data & Analytics employers · All rankings
Pay compared with the market
This listing does not state pay. Across 35 open ai engineer listings that state pay, the middle half runs $140,000 to $226,500 and the median is $176,000.
Listed pay is what employers advertise, not what people are paid.
How AI is used in this kind of work
Among computer and information research scientists, AI is already used for a large share of the tasks. Measured exposure for computer and information research scientists: 34% (high).
Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.
Skills this job asks for
Say which you have and which you want to build. We use it to match you to jobs like this one.
About the job
ABOUT DISTYL AI
Distyl is an applied AI technology company partnering with the world’s most ambitious institutions to rearchitect critical operations for the frontier of AI. Our customers include the largest companies in telecom, healthcare, insurance, manufacturing, consumer goods, and global social organizations.
We research and deploy technologies that power AI-native operations — both for our partners and for Distyl itself. Our work spans research into self-constructing systems, the development of the most reliable execution of AI systems, and products that transform mission-critical workflows. As a result, Distyl's technologies affect some of the world's largest operations — from hundreds of millions of consumer interactions to tens of millions of supply chain transactions and millions of patient journeys.
Distyl is backed by leading investors including Lightspeed Venture Partners, Khosla Ventures, Coatue, DST Global, and the board-members of 20+ F500s.
WHAT WE ARE LOOKING FOR
AI Engineers build and operate production AI systems that deliver business value inside customer environments. This role is for engineers who thrive in ambiguous problem spaces, take ownership of outcomes, and want to work directly on AI systems that must perform reliably under enterprise constraints.
AI Engineers are hands-on builders. They design, implement, deploy, and iterate on end-to-end AI systems in close partnership with customers, subject matter experts, and other Distyl engineers. They translate messy operational needs into concrete system behavior, build the software and AI workflows required to support that behavior, and continuously improve systems through evaluation, feedback, integration, and production iteration.
This is not a demo-building role. AI Engineers are expected to make AI systems work in practice: with users, data, constraints, and accountability for production outcomes.
KEY RESPONSIBILITIES
- Build and operate AI systems deployed in customer environments, taking ownership of system behavior, reliability, and usefulness in production
- Design and implement compound AI workflows that combine models, prompts, agents, tools, retrieval, evaluation, feedback loops, and execution into coherent production systems aligned with user and SME needs
- Develop clean, maintainable Python services and application logic that integrate AI capabilities into customer workflows, data platforms, APIs, and existing applications
- Operate on live systems by measuring behavior, identifying failure modes, debugging issues, and iterating rapidly to improve quality, reliability, and user value
- Build evaluation frameworks, test cases, feedback mechanisms, and observability patterns that help teams understand and improve AI system performance over time
- Work directly with customer stakeholders and subject matter experts to understand workflows, clarify requirements, reason about tradeoffs, and adapt systems as needs evolve
- Use AI-native engineering tools to accelerate implementation, debugging, experimentation, data analysis, and system improvement
- Collaborate with other AI Engineers, AI Strategists, and other Distillers to make pragmatic system design decisions that balance speed, robustness, maintainability, and customer impact
- Take accountability for the production outcomes of the components, workflows, and systems you build
WHAT WE REQUIRE
- 5+ years of software engineering experience
- Ownership mentality for AI systems. You take responsibility for whether the systems you build deliver their intended value in production. You are comfortable making technical decisions, learning from system behavior, and owning the results of your work
- Experience building AI systems. You have built applications powered by LLMs or other AI models and are comfortable composing multiple components — prompts, agents, tools, retrieval, evaluators, workflows, and integrations — into end-to-end systems. You reason about system behavior holistically rather than treating models as black boxes
- Strong engineering fundamentals. You write clean, maintainable Python and are comfortable building production software systems. You understand core engineering concepts like versioning, debugging, testing, performance, code review, and production readiness
- AI-native working style. You use AI tools daily to write and debug code, explore designs, analyze data, and automate repetitive work. You are curious about new model capabilities and techniques, and actively incorporate them into how you build and iterate on systems
- Comfort in customer environments. You are able to work directly with customer teams, ask good questions, and adapt quickly to new domains. You communicate clearly about system behavior, limitations, and tradeoffs, and can operate effectively in high-trust, high-visibility situations
- Pragmatic delivery mindset. You can navigate ambiguity, make progress with incomplete information, and balance speed with robustness when building systems that need to work for production users
- Willingness to travel. Travel is typically 10–30%, depending on the project, customer needs, and your role on the engagement
WHAT WE OFFER
- The base salary range for this role is $180K – $250K, depending on experience, location, and level. In addition to base compensation, this role is eligible for meaningful equity, along with a comprehensive benefits package
- 100% coverage of medical, dental, and vision insurance for employee and dependents
- Flexible time off
- Retirement and financial planning benefits, including access to pre-tax HSA, FSA, and commuter accounts, 401(k), and financial coaching resources
- Comprehensive wellness benefits, including physical fitness, mental well-being, and fertility and family-building benefits through Carrot
- Complimentary in-office lunches and snacks provided
- Access to state-of-the-art AI models, generous usage of modern AI tools, and real-world business problems
- Ownership of high-impact projects across top enterprises
- A mission-driven, fast-moving culture that values curiosity, pragmatism, and excellence
Distyl has offices in San Francisco and New York. This role follows a hybrid collaboration model with 3+ days per week (Tuesday–Thursday) in‑office.
#LI-Hybrid
We believe diverse perspectives make our work stronger and more impactful. We are an equal opportunity employer and evaluate all applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other legally protected characteristic. We encourage candidates from all backgrounds to apply.