AI Solutions Engineer, Talent Acquisition

Anduril Anduril · Defense · Seattle, WA · People : Talent Acquisition : TA Operations

The role is an AI Solutions Engineer focused on building AI agents and automations within the Talent Acquisition function. The individual will own the AI and automation roadmap, conduct build-vs.-buy assessments, and ensure safety, compliance, and governance of AI systems. Requires strong applied AI engineering and software engineering skills, with a focus on production systems.

What you'd actually do

  1. Build AI agents and automations that solve real recruiting problems — sourcing, screening, outreach, scheduling, candidate research, pipeline operations, reporting — with measurable ROI tied to recruiter time saved, funnel improvements, or hiring outcomes.
  2. Own TA's AI and automation roadmap end-to-end — prioritization, sequencing, communication, and progress read-outs to TA leadership and stakeholders.
  3. Partner closely with Anduril's Corporate Technology team to understand the company's AI tooling, model access, infrastructure, security posture, and roadmap — and design solutions that ride those rails rather than fight them.
  4. Form and defend a clear point of view on where AI and automation will and won't drive value across the recruiting function, and proactively surface opportunities the team hasn't asked for yet.
  5. Lead rigorous build-vs.-buy assessments — evaluating vendors, internal platforms, and custom builds against scalability, total cost, safety, compliance, and long-term maintainability.

Skills

Required

  • 4+ years of hands-on technical experience building production software
  • 1–2 years of that focused on applied AI / LLM-based systems (agents, tool use, RAG, evaluations, automations)
  • Strong software engineering fundamentals — APIs and integrations, version control, testing, CI/CD, basic infrastructure, and deployment
  • Production experience building AI agents or LLM-driven automations for use across a growing team (250+ people)
  • Prompt design
  • Tool use
  • Retrieval
  • Evaluation
  • Understanding of failure modes in non-deterministic systems

Nice to have

  • Genuinely curious about the recruiting / TA domain
  • Prior experience in recruiting / TA strongly preferred
  • Willingness to sit with recruiters and sourcers, learn their workflows, and build for _their_ problems

What the JD emphasized

  • build AI agents and automations
  • applied AI engineering chops
  • LLMs
  • agentic workflows
  • tool use
  • retrieval
  • evals
  • real software engineering rigor
  • Python
  • APIs
  • integrations
  • version control
  • testing
  • deployment
  • regulated environment
  • build-vs.-buy assessments
  • safety
  • compliance
  • governance posture
  • ITAR/CUI considerations
  • production software
  • LLM-based systems
  • prompt design
  • failure modes

Other signals

  • Build AI agents and automations that solve concrete recruiting problems
  • Own TA's AI and automation roadmap end-to-end
  • Applied AI engineering chops (LLMs, agentic workflows, tool use, retrieval, evals)