Senior Applied AI Engineer (Agentic Systems)

Clera

$185K — $210K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 7+ years professional experience in software/ML engineering with increasing responsibility.
  • Expertise in architecting multi-agent AI systems and defining agent roles.
  • Strong background in LLM application development and production deployment of AI systems.
  • Experience with RAG pipelines and graph-based retrieval systems.
  • Familiarity with stateful workflow orchestration applied to distributed AI workloads.
  • Experience in startup environments or regulated industries like healthcare or finance.
  • Willingness to work in-office in San Francisco at least 3 days a week.

Responsibilities

  • Design and evolve multi-agent LLM systems for compliance review tasks.
  • Define agent responsibilities and minimize reasoning drift in workflows.
  • Architect retrieval pipelines to deliver context to agents.
  • Manage stateful, fault-tolerant workflows using systems like Temporal.
  • Build evaluation frameworks to ensure system reliability and correctness.
  • Collaborate on preprocessing to ensure agents receive structured context.
  • Focus on practical solutions rather than research-oriented approaches.

Benefits

  • Equity participation in a well-funded, early-stage company.
  • Opportunity to define technical architecture of a groundbreaking product.
  • Work alongside a senior, high-caliber team.
Full Job Description
About the Role

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.
What You'll Do

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.
What We're Looking For

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.
Compensation & Benefits
  • 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.
Location
  • 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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