Senior AI Engineer – Core

Own the evaluation layer for Hilbert’s production agents, including harnesses, metrics, golden datasets, regression gates, and human-in-the-loop review Architect and implement agent workflows using LangChain, LangGraph, or equivalent frameworks Build state memory, routing, tool registries, and recovery paths Own systems from experimentation through production Operate production systems through tracing, monitoring, latency management, cost-per-task budgeting, and on-call Diagnose production failures and turn them into durable fixes and tests Expand agent capabilities across retrieval, orchestration, and execution Set technical standards, review designs, and define reusable patterns Collaborate with the founding team and cross-functional partners Communicate technical decisions, tradeoffs, and progress clearly Make pragmatic engineering decisions, ship, learn, and iterate Build intelligent retrieval combining RAG, graph-based retrieval, and other approaches Develop robust agentic workflows that handle edge cases, missing data, escalation, and human-in-the-loop checkpoints Integrate agents with external platforms and execute real-world workflows Requirements

6+ years of production software engineering experience 2+ years building LLM or agent systems used by real users in production Experience with APIs, services, data infrastructure, tests, CI/CD, and on-call Hands-on experience with LangChain, LangGraph, or equivalent agent/orchestration frameworks Experience with agent architectures, state memory, routing, tool registries, recovery paths, and multi-step inference Ability to design evaluation harnesses, metrics, golden datasets, regression gates, and human-in-the-loop review Ability to diagnose hallucination, tool misuse, retrieval misses, and silent degradation Strong knowledge of retrieval-augmented generation, hybrid and graph retrieval, chunking, embeddings, ranking, and grounding Experience with LLM observability tools such as Langfuse or OpenTelemetry Knowledge of cost and latency optimization Knowledge of MCP, tool-calling frameworks, structured output, and constrained decoding Clear technical communication and ability to explain architecture tradeoffs Ability to take ownership and work effectively in ambiguity and at startup speed Willingness to commute to the San Francisco office for a hybrid work schedule Authorization to work in the United States without visa sponsorship Core Competencies

Demonstrates expertise in architecting and implementing agent workflows using LangChain or LangGraph, with a strong focus on production software engineering and LLM systems. Capable of optimizing performance through effective monitoring, diagnostics, and technical communication. Highest-signal resume keywords

LangChain Framework LangGraph Framework Production Software Engineering LLM Systems Development Retrieval-Augmented Generation ATS Optimization Keywords

Hard Skills

APIs Data Infrastructure CI/CD Agent Architectures State Memory Routing Tool Registries Recovery Paths Evaluation Harnesses Metrics Soft Skills

Clear Technical Communication Ownership Ability to Work in Ambiguity Industry Keywords

Production Systems Human-in-the-Loop Review Cost Optimization Latency Management Hybrid Retrieval Tools & Technologies

Langfuse OpenTelemetry

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