Staff AI Software Engineer

We're partnered with a high-growth, mission-driven SaaS company transforming how businesses build and maintain trust, with AI at the core of their next phase of innovation. The platform is redefining how critical enterprise workflows are automated, particularly in areas where reliability, auditability, and security are essential.

This is a high-impact role where you will help define how AI is architected across the company. You won't just be building features. You'll make foundational decisions around systems, evaluation, and long-term technical direction, working across LLMs, retrieval systems, and agent-based workflows in production environments.

What You'll Do

Design and own production AI systems end-to-end, including LLM pipelines, retrieval systems, and orchestration layers

Build and scale RAG systems, reranking pipelines, and vector-based search infrastructure

Define evaluation frameworks to measure retrieval quality, reasoning accuracy, and system performance

Analyze production behavior, identify failure modes, and drive improvements based on data

Make key architectural decisions across model infrastructure, tooling, and workflows

Partner closely with product, platform, and domain teams to translate complex requirements into scalable systems

Lead best practices for building reliable, observable, and cost-efficient AI systems

Requirements

10+ years of software engineering experience, including 3+ years working on ML or AI systems

Proven experience owning and deploying production LLM systems

Strong background in RAG, embeddings, reranking, and vector databases (e.g., Pinecone, FAISS, Chroma)

Experience designing evaluation systems and improving models through quantitative analysis

Strong Python skills, with solid software engineering fundamentals

Experience making architectural decisions that influence team or org direction

Strong understanding of production systems, including reliability, observability, and cost tradeoffs

Ability to break down ambiguous problems and operate with a high degree of ownership

Clear communication skills and experience working cross-functionally

Nice to Have

Experience in regulated domains such as compliance or security

Familiarity with data platforms or analytics tooling

Experience with orchestration frameworks (e.g., Temporal, Airflow)

Exposure to LLM evaluation platforms or tooling

Contributions to open source, research, or technical communities

If you're interested in shaping how AI systems are built, evaluated, and deployed in high-trust environments, this is an opportunity to have direct influence on both technical direction and real-world impact at a fast-growing company.

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