Own the behavior and performance of AI systems deployed for customers
Design and implement compound AI workflows that combine models, agents, retrieval, evaluation, and execution into coherent, production-ready systems aligned with real SME needs
Operate on live systems, measuring behavior, identifying failure modes, and iterating rapidly to improve quality, reliability, and usefulness. This includes designing prompts and agent logic, building evaluation frameworks, integrating feedback loops, and using AI-driven tools to accelerate debugging and experimentation
Integrate AI systems into customer data platforms, APIs, and existing applications. You'll make pragmatic system design decisions that balance speed, robustness, and maintainability, and ensure systems remain understandable and operable over time
Work directly with customer stakeholders—often in high-visibility settings—and are expected to reason clearly about system behavior, tradeoffs, and limitations.
Take accountability for outcomes in production and adapt systems as requirements evolve
Requirements
2+ years of software engineering experience
Ownership Mentality for AI Systems: You take responsibility for whether an AI system actually delivers its intended value in production. You are comfortable making independent technical decisions across system design, evaluation, and integration, and owning the results of those decisions
Experience Building AI Systems, Not Just Calling APIs: Built applications powered by LLMs or other AI models and are comfortable composing multiple components—prompts, agents, tools, retrieval, evaluators—into end-to-end systems. You reason about system behavior holistically rather than treating models as black boxes
Strong Engineering Fundamentals: Write clean, maintainable Python and are comfortable building and operating real systems. You understand core engineering concepts like versioning, debugging, testing, and performance, and can build systems that hold up under real usage and scrutiny
AI-Native Working Style: 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: Able to work directly with customer teams, ask good questions, and adapt quickly to new domains. You communicate clearly about system behavior and limitations, and can operate effectively in high-trust, high-visibility situations
Travel: Ability to travel 25-50%
Tech Stack
Python
Benefits
100% covered medical, dental, and vision for employees and dependents
401(k) with additional perks (e.g., commuter benefits, in‑office lunch)
Access to state‑of‑the‑art 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 prizes curiosity, pragmatism, and excellence