Staff AI Engineer (Agentic Systems)

TL;DR

Staff AI Engineer (Agentic Systems): Building production-grade agentic systems to audit medical claims by reasoning over clinical guidelines and raw medical records with an accent on human-expert accuracy and long-context document processing. Focus on designing agent topologies, building robust evaluation harnesses, and translating ambiguous business problems into technical implementations.

Location: Remote - US (Hybrid preferred with a strong preference for in-office collaboration)

Salary: $180k–$260k+

Company

A leading healthcare intelligence company delivering AI-powered platforms to maximize financial outcomes and reduce healthcare costs for health plans.

What you will do

• Drive ambiguous business problems to closure by collaborating with clinical and product leads to define success metrics.
• Build comprehensive evaluation harnesses to measure recall, appeal-survival rates, and cost per case before shipping.
• Set technical direction for problem areas, including agent topology, context strategy, model mix, and deterministic guardrails.
• Implement agent engineering best practices such as structured outputs, citation grounding, and cost/latency control.
• Act as the technical interface to business stakeholders, defending methodologies and interpreting domain-specific requirements.
• Leverage AI tooling (Claude Code, Codex) as a force multiplier to accelerate planning, scaffolding, and refactoring.

Requirements

• Must be based in the United States (E-Verify participating employer).
• 6+ years of applied ML/AI/software engineering experience (or 4+ years with a Master's/PhD).
• Proven track record of owning at least two production systems from ambiguity to measured impact, including LLM or agent-based systems.
• Deep hands-on experience with agent SDKs (OpenAI, Anthropic, LangGraph) and strong Python engineering skills.
• Experience designing agent loops, context engineering, and building reproducible eval harnesses.
• Proficiency with VS Code and git workflows (branches, rebases, worktrees).

Nice to have

• Experience with long-context, citation-grounded systems in high-stakes domains like healthcare, legal, or finance.
• Technical leadership experience, including mentoring engineers and reviewing architectural designs.
• Familiarity with reasoning models (o-series, Claude extended thinking) and production LLM observability.
• Knowledge of document understanding, OCR, layout-aware models, or multimodal retrieval.

Culture & Benefits

• Competitive salary and meaningful equity in a fast-growing startup.
• Comprehensive Medical, Dental, and Vision insurance with FSA/HSA options.
• 401(k) with company match and tuition reimbursement.
• Unlimited PTO.
• Flexible and trusting work environment that empowers autonomy.