Senior AI Engineer

The Senior AI Engineer will architect and build the agentic backend for a multi-year engagement requiring substantial expertise across distributed databases, machine learning, and production agentic systems. Architectural decisions established in the early phase of the engagement will define the technical foundation of the program for the duration of its lifecycle.

Responsibilities

• Architect the data and retrieval layer end-to-end, including schema design, indexing, query planning, evaluation, and observability for systems operating under significant production load.
• Design and implement the agentic core, including model selection, retrieval pipelines, tool routing, evaluation harnesses, and the production controls required for reliable operation at scale.
• Lead foundational technical decisions that establish the long-term architecture and engineering direction of the program.
• Partner closely with a co-founder and the forward-deployed engineering team to translate client requirements into a robust, scalable production system.

Qualifications

• Deep expertise in databases and data systems. Demonstrated experience designing and operating production data systems at scale, including query planners, indexing strategies, distributed storage, and performance tuning. Proven track record diagnosing and resolving issues that emerge at high scale.
• Senior-level machine learning and agentic systems experience. Production experience with retrieval pipelines, evaluation frameworks, and agentic orchestration, with sound judgment regarding the appropriate application of each.
• Infrastructure-grade engineering rigor. Disciplined consideration of latency, reliability, cost, and failure modes throughout the design and implementation process. Experience with large-scale systems where correctness and performance are equally critical, such as search infrastructure, large-scale data platforms, or comparable domains.
• Seven or more years of senior engineering experience, including ownership of production systems relied upon by other teams and stakeholders.
• Experience operating in ambiguous, foundational engineering environments. Ability to decompose complex, novel technical problems into clear workstreams and deliver against them.