Senior Applied AI Engineer (Agentic Systems)

About the Role

This is a founding-level, senior individual contributor role at a Series A AI compliance SaaS company building the system of record for enterprise marketing and packaging review. The platform automates high-stakes compliance workflows - turning manual, multi-week approval cycles into hours - for large regulated-industry brands.

As a Senior Applied AI Engineer focused on Agentic Systems, you will own the core technical moat: the deterministic orchestration layer and safety infrastructure that makes enterprise-grade AI compliance trustworthy at scale. You are not building demos - you are building auditable, production-grade systems where correctness is non-negotiable.

This is a hybrid, in-office role based in San Francisco, CA (3 days/week in-office). You will work directly alongside a small, senior engineering team at a critical architectural inflection point.

What You'll Do

Agentic Reasoning & Orchestration: Design and evolve multi-agent LLM systems that decompose complex review tasks into reliable, auditable steps. Define agent responsibilities, hand-offs, and termination conditions to minimize reasoning drift and maximize consistency.

Context, Retrieval & Memory Systems: Architect retrieval pipelines using RAG, structured memory, and graph-based retrieval approaches to supply agents with the right context at the right time. Balance recall, precision, and latency across large knowledge bases (brand guidelines, regulations, historical decisions).

Stateful, Asynchronous Workflows: Own long-running, fault-tolerant workflows using Temporal (or similar), ensuring retries, versioning, and determinism across non-deterministic model calls. Treat agent orchestration as a distributed systems problem - managing state, failures, and observability.

Evaluation, Safety & Reliability: Build evaluation frameworks using statistical metrics, gold labels, and automated regression testing to prove system reliability. Prioritize correctness and trust, especially in high-risk legal and compliance scenarios.

Asset Understanding Pipeline: Collaborate on image and document preprocessing (OCR, layout analysis, Vision Language Models) to ensure downstream agents receive structured, machine-readable context.

What We're Looking For

Required

7+ years of professional software/ML engineering experience

Minimum 2-year average tenure across roles, with a clear track record of career progression and promotions

Demonstrated expertise architecting multi-agent AI systems: agent role design, multi-step reasoning flows, tool integration, memory/retrieval architectures, and deterministic/auditable workflows

Hands-on experience with LLM orchestration frameworks and stateful workflow engines (e.g., Temporal, Prefect, or equivalent)

Strong background in retrieval-augmented generation (RAG) and vector/graph-based retrieval systems

Experience building and owning production-grade evaluation and safety frameworks for AI systems

Startup experience or equivalent experience in CPG, regulated industries, or enterprise compliance domains

Must be eligible to work in the United States without visa sponsorship

Able and willing to work in-office in San Francisco, CA at least 3 days per week

Nice to Have

Experience with vision-language models (VLMs), OCR pipelines, or document layout analysis

Background in marketing technology, packaging compliance, or regulatory tech (regtech)

Familiarity with enterprise compliance workflows or brand governance processes

Prior experience as a founding or early-stage engineer

Compensation & Benefits

Base salary: $185,000 – $210,000 per year

Equity participation (early-stage, Series A)

Hybrid work flexibility (3 days in-office, remainder remote)

Visa sponsorship is not available for this role. Candidates must be authorized to work in the United States.

Location

San Francisco, CA, United States - Hybrid (3 days/week in-office required). Some remote flexibility on remaining days.