Senior AI Engineer, MapGPT

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior AI Engineer, MapGPT based in United States. The Senior AI Engineer, MapGPT will design and deliver multi-component AI systems that power advanced location, search, navigation, and developer experiences. You will work across teams and technology stacks, focusing your expertise on high-priority AI challenges wherever they have the greatest impact. The role combines software engineering, data engineering, LLM systems, evaluation, agent orchestration, and production operations. You will own technical design and delivery while establishing robust measurement frameworks for systems with non-deterministic behavior. Your work will span data pipelines, model and tool boundaries, evaluation systems, feedback loops, and performance optimization. This is a hands-on senior individual contributor role in an environment where many technical questions are still evolving and where practical experimentation is encouraged. You will also help raise engineering standards through design reviews, mentorship, and shared tooling while participating in 24/7 on-call coverage. Accountabilities: - Define technical approaches for AI-powered products, establish measurement frameworks, and build evaluation systems for non-deterministic behavior. - Develop datasets, hypotheses, evaluation criteria, and regression gates to determine whether system changes produce correct and reliable results. - Continuously evaluate APIs, SDKs, data representations, and reference applications from the perspective of developers, agents, and end users. - Identify issues such as incorrect parameter usage, integration anti-patterns, and other product gaps, recommend improvements, and drive fixes through to completion. - Own MVP delivery against an agreed technical design while balancing long-term technical quality with the need to ship useful increments quickly.

- Build and maintain data pipelines and supporting tooling, including ingestion, conflation, entity resolution, quality checks, and batch and streaming processing. - Evaluate external datasets, models, benchmarks, research, and open-source technologies, deciding when to adopt existing solutions versus building internally. - Design feedback loops that turn product usage into data for continuous improvement and convert recurring failures into evaluation cases. - Define the boundary between models and the tools they call, including what the model handles, what it delegates, and how context is maintained. - Build and improve model harnesses and agent orchestration systems while addressing issues such as stale context, hallucinated arguments, partial success, and unbounded loops. - Optimize systems against latency and cost targets through streaming, partial results, caching, model routing, and prompt design. - Build internal developer tools and harnesses, including CLI and MCP-based tooling, and share reusable components across teams. - Contribute to code and design reviews while mentoring engineers on evaluation practices and high-quality AI system development. - Help investigate and solve emerging technical challenges where established approaches may not yet exist. - Participate in an on-call rotation supporting system availability 24/7, including potential response requirements outside normal working hours and on weekends. Requirements: - Bachelor's degree in a STEM discipline and 5+ years of software engineering experience with production ownership of services, pipelines, SDKs, or comparable systems. - 2+ years of experience shipping LLM-backed features to real users in production environments with customers, error budgets, and on-call responsibilities. - Strong data engineering foundation, including SQL, at least one distributed processing framework, and experience building pipelines where data accuracy and correctness are critical.