SAIC behavioral interview for AI Engineer (Engineering, 10k+ employees)

This behavioral interview at SAIC assesses mission-first mindset, ethical decision-making, and collaboration in secure, highly regulated environments typical of defense, space, civilian, and intelligence programs. Expect a structured STAR-style conversation with a 2–3 person panel (e.g., hiring manager, AI/ML technical lead, program/engineering manager). Focus areas: - Mission impact: examples where you translated AI capabilities into measurable outcomes for a customer mission (e.g., latency, accuracy, reliability, cost/schedule). - Responsible/secure AI: handling sensitive or classified data, data provenance, model risk, auditability, bias/mitigation, and alignment to government AI ethics and security expectations; trade-offs you made under compliance constraints. - Delivery in constraints: deploying models in air-gapped or resource-limited environments, working with GOTS/COTS tools, navigating ATO/RMF or similar processes, and sustaining models via MLOps in government clouds. - Stakeholder management: partnering with government CORs/PMs, integrators, and vendors; communicating complex AI decisions to non-technical stakeholders; negotiating scope changes and priorities. - Teaming and leadership: leading without formal authority across multi-disciplinary, geographically distributed, and mixed-cleared teams; mentoring, code/data review habits, and continuity planning. - Adaptability and integrity: responding to shifting requirements/funding, documenting decisions, writing after-action reports, and escalating risks early. Interviewers probe for specifics (your role, constraints, metrics) and follow up with scenario-based what-would-you-do questions grounded in SAIC’s integrator role and partner ecosystem.