AI Solutions Engineer, Talent AcquisitionNew$171K
The opportunity
Anduril Industries is a defense technology company with a mission to transform U. S.
What you'll do
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.
Own TA's AI and automation roadmap end-to-end: prioritization, sequencing, communication, and progress read-outs to TA leadership and stakeholders.
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.
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.
Lead rigorous build-vs.-buy assessments: evaluating vendors, internal platforms, and custom builds against scalability, total cost, safety, compliance, and long-term maintainability.
Ship pragmatically: strategically prioritized initiatives most of the time, but also fast, home-grown solutions for ad hoc team requests when that's the rightcall.
What they're looking for
- Partner with the TA Enablement team to drive baseline AI literacy across the: recruiting org — internal training, documentation, prompt patterns, guardrails, and best practices that recruiters and sourcers can actually use.
- Own the safety, compliance, and governance posture of every AI and automation: system you ship — PII handling, role-based access, audit trails, model risk, data residency, and ITAR/CUI considerations where applicable.
- Define and instrument success metrics for every shipped system: adoption, time saved, quality, error rates, cost per outcome — and retire what isn’t working.
- Establish lightweight engineering practices for the function: version control, testing, evals, deployment, monitoring — so AI work is durable rather than throwaway.