Forward Deployed Engineer; Agentic Systems Founding

We’re hiring a Forward Deployed Engineer (FDE) to deploy autonomous AI agents into real enterprise workflows. This is a ship-the-product-in-the-field role: you’ll work directly with customers to map messy processes, build and integrate agentic systems (tools + planning + memory), and own production reliability end-to-end.

We’re looking for someone with hands-on experience shipping agentic workflows (tools + planning + state/memory) and the engineering rigor to support them in production (evals + observability)

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• Design and build agentic systems with tool calling, planning/execution loops, state/memory, and human-in-the-loop (HITL) controls
• Implement reliability mechanisms: retries, timeouts, checkpointing, idempotency, and safe failure modes
• Build enterprise integrations (e.g., Slack/Jira/Salesforce/Service Now/SQL/SharePoint/knowledge bases), including auth, permissions, and auditability
• Create evaluation and monitoring systems: offline regression suites, dataset replay, and production quality/cost/latency dashboards
• Debug real failures in production: non-determinism, flaky tools, prompt regressions, partial outages, and “agent got stuck” scenarios
• Collaborate with the founding team to shape product roadmap, technical strategy, and deployment playbooks

• Long-running agent workflows with persistent state and memory across sessions
• Orchestration patterns for multi-step, multi-tool processes
• Guardrails, verification, and human approval gates for high-stakes actions
• Reliability + observability (tracing, structured logs, prompt/tool versioning, replay)
• Enterprise security requirements: access control, audit logs, compliance constraints
• Evaluation and benchmarking of agent performance in real production environments

• Proof you’ve shipped agentic systems: built and deployed at least one system that includes tool use + planning + state/memory + reliability mechanisms (work or OSS)
• Experience with evaluation of LLM/agent behavior (task suites, regression tests, acceptance metrics, quality thresholds)
• Strong software engineering fundamentals (Python and/or Type Script), API integrations, and systems thinking
• Comfortable working directly with customers and owning outcomes end-to-end (Forward Deployed / customer-zero mentality)
• Willingness to work onsite in Chatsworth, California

• Experience with agent frameworks (e.g., Lang Graph, Lang Chain, Llama Index, Auto Gen, CrewAI, DSPy) in real deployments
• Workflow engines for long-running processes (e.g., Temporal/Cadence, Airflow/Dagster as applicable)
• Built agent observability:
  Open Telemetry-style traces, replay pipelines, prompt/version registries, cost/latency instrumentation
• Experience with enterprise software integration patterns and security/compliance constraints (PII, access control, auditability)
• Familiarity with fine-tuning and adaptation methods (RAG, routing, lightweight fine-tunes, tool augmentation)

• You love deploying real systems into messy environments and iterating fast
• You think in systems: failure modes, tradeoffs, correctness, reliability, scalability
• You’re pragmatic and execution-oriented, but you care deeply about engineering quality
• You’re excited about the limits of agents and motivated to push them responsibly in production
• You can communicate clearly with both technical teams and enterprise stakeholders

• Competitive compensation + meaningful equity, aligned with early-stage risk/reward
• Direct access to the founding team and high ownership from day one
• Resources to ship: strong engineering support and the compute/tools needed to deploy real agentic systems
• A high-velocity…