Senior Applied AI Engineer (Agentic Systems)
Clera · Full-time · Posted 1w ago
This is a founding-level senior engineering role at a fast-growing, Series A/B-stage B2B SaaS company in the AI compliance and regulatory technology space. The company automates high-stakes marketing and packaging review workflows for enterprise brands in regulated industries — turning lengthy manual approval cycles into fast, auditable, AI-driven processes.
As a Senior Applied AI Engineer (Agentic Systems), you will own the technical core of the platform: a safety-focused, deterministic multi-agent orchestration system purpose-built for enterprise compliance. This is a hands-on, in-office role in San Francisco where correctness and trust matter more than demos. You'll work closely with a small, senior team and have an outsized impact on the product's technical direction.
Agentic Reasoning & Orchestration
Design and evolve multi-agent LLM systems that decompose complex compliance review tasks into reliable, auditable steps.
Define agent responsibilities, hand-offs, and termination conditions to minimize reasoning drift and maximize consistency across enterprise workflows.
Context, Retrieval & Memory Systems
Architect retrieval pipelines using RAG, structured memory, and graph-based retrieval to deliver the right context (brand guidelines, regulations, historical decisions) to agents at the right time.
Balance recall, precision, and latency across large, evolving knowledge bases.
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 end-to-end.
Evaluation, Safety & Reliability
Build evaluation frameworks using statistical metrics, gold labels, and automated regression testing to prove and maintain system reliability.
Prioritize correctness and trust, particularly 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.
Focus on practical, production-grade solutions over research-oriented approaches.
Required
7+ years of professional software/ML engineering experience, with a clear progression of increasing scope and responsibility.
Demonstrated expertise architecting multi-agent AI systems: defining agent roles, multi-step reasoning flows, tool integration, memory/retrieval architectures, and deterministic, auditable workflows.
Strong background in LLM application development and production deployment of AI systems (not just prototyping).
Experience with RAG pipelines, vector stores, and/or graph-based retrieval systems.
Familiarity with stateful workflow orchestration (e.g., Temporal, Prefect, Airflow) applied to distributed AI workloads.
Experience at a startup — or, alternatively, strong exposure to regulated industries (e.g., consumer packaged goods, healthcare, financial services).
Ability and willingness to work in-office in San Francisco, CA at least 3 days per week.
Must be eligible to work in the United States without visa sponsorship (no sponsorship available).
Nice to Have
Experience with vision-language models (VLMs), OCR pipelines, or document layout analysis.
Background in compliance, regulatory technology, or marketing/packaging review workflows.
Familiarity with evaluation frameworks for LLM-powered systems (e.g., RAGAS, custom eval harnesses).
Prior experience in a founding engineer or technical lead capacity.
Salary: $185,000 – $210,000 per year, depending on experience.
Equity participation in a well-funded, early-stage company at an inflection point.
Opportunity to define the technical architecture of a category-creating product alongside a senior, high-density team.
San Francisco, CA — hybrid (in-office 3 days/week, with remote flexibility the remaining days).
Visa sponsorship is not available; candidates must be authorized to work in the United States.
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