Forward Deployed Engineer (Agentic Systems)

Position Overview

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).

About Us

We’re a stealth-stage startup building enterprise-grade AI agent platforms that automate long-running, knowledge-intensive processes. Our focus is on systems that can:

• Understand organizational context
• Integrate with existing workflows and enterprise software
• Maintain coherent state and knowledge across extended interactions
• Operate reliably in production with measurable business outcomes

This is not chatbot tech — it’s the infrastructure layer for the next generation of enterprise software.

Role & ResponsibilitiesCore Responsibilities

• Own 0→1 enterprise deployments: discovery → prototype → production rollout → iterate until measurable ROI
• 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/ServiceNow/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

Technical Problem Areas (Not Exhaustive)

• 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

Required Qualifications

• 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)
• Production engineering mindset: tracing/logging, incident-style debugging, rollout/rollback strategies, versioning prompts/tools
• Strong software engineering fundamentals (Python and/or TypeScript), 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

Preferred Qualifications

• Experience with agent frameworks (e.g., LangGraph, LangChain, LlamaIndex, AutoGen, CrewAI, DSPy) in real deployments
• Workflow engines for long-running processes (e.g., Temporal/Cadence, Airflow/Dagster as applicable)
• Built agent observability: OpenTelemetry-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)

Who You Are

• 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

What We Offer

• 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 environment where you’ll help define the product, the architecture, and the deployment playbook
• Benefits and perks will be finalized as we scale, and we’ll share specifics during the process

Culture & Environment

• Direct access to the founding team and fast, collaborative decision-making
• Opportunity to shape product direction and deployment strategy from day one
• Fast-paced environment with high ownership and high impact

Location

Onsite in Chatsworth, California with core collaboration hours expected. We believe proximity matters for early-stage execution, especially while defining architecture, product, and deployment playbooks.

Application Process

Submit the following:

• Resume highlighting relevant experience with AI/ML systems and any architectural or design work
• Brief cover letter (1-2 paragraphs) explaining your interest in agentic AI, what specific problems excite you, and your approach to systems design
• Link to portfolio, GitHub, or relevant work samples (optional but strongly encouraged)
• For recent grads: thesis abstract, system design projects, or significant architectural work if applicable

Pay: $120,000.00 - $210,000.00 per year

Benefits:

• 401(k)
• Dental insurance
• Health insurance
• Life insurance
• Paid time off
• Vision insurance

Application Question(s):

• Have you built and shipped a 0→1 product, tool, or workflow yourself? Briefly describe it and the technologies used.
• Have you worked with LangChain, AI agents, or multi-agent AI workflows? If yes, briefly describe what you built.
• Describe your experience in consulting, PM, AM, sales, or engineering roles where you managed work independently without constant direction.

Work Location: In person