AI Engineer

Los Angeles, CA, US • Posted 7 days ago • Updated 7 days ago
Full Time
Occasional Travel Required
On-site
100000 - 160000/yr
Fitment

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Job Details

Skills

  • Python
  • agentic
  • RAG
  • ML
  • LLM

Summary

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 & Responsibilities

Core 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.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: dicects
  • Position Id: 9009592
  • Posted 7 days ago
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Alex Kern

Recruiter @ Dice Talent & Staffing Solutions
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