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

Titan Holdings Group

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