AI Engineer - Industry

AI Engineer, Financial Services / Healthcare

Experience: 3–5 years · Location: Remote · Openings: 3–5

About the role

Everything in Role 1, applied to regulated domains. You''ll build AI systems where a wrong output has real consequences — a mispriced position, a missed clinical flag, a compliance finding. We need engineers who already understand that context and won''t have to learn on the client''s time why an audit trail matters or why PHI can''t sit in a prompt log.

What you''ll do

All Role 1 responsibilities, plus:

• Translate domain workflows  claims adjudication, prior authorization, clinical documentation, KYC/AML, credit and risk analysis, reconciliation, regulatory reporting into AI-assisted systems.
• Design for compliance from the start: PHI/PII handling, data residency, de-identification, encryption in transit and at rest, least-privilege access, retention policy, and complete audit logging of model inputs and outputs.
• Build human-in-the-loop patterns where full automation isn''t appropriate review queues, confidence thresholds, escalation paths, override tracking.
• Implement domain-specific evaluation: accuracy against clinician- or analyst-reviewed ground truth, bias and fairness checks, explainability sufficient to satisfy internal risk and model governance review.
• Work with compliance, legal, risk, and clinical or business SMEs as regular collaborators, not as a final approval gate.

Mandatory skills

• All Role 1 mandatory skills.
• 2+ years building software in financial services or healthcare banking, capital markets, insurance, payments, fintech, or provider/payer/health-tech. Delivered production systems in one of these domains, not adjacent exposure.
• Working knowledge of the relevant regulatory environment HIPAA / HITRUST / HL7 / FHIR for healthcare; SOX, PCI DSS, GLBA, SEC/FINRA, KYC/AML, or Basel-type frameworks for finance. You don''t need to be a compliance officer, but you need to know what constrains the design.
• Secure data handling practice  has worked under PHI or PII restrictions and can speak to concrete controls, not just principles.
• Ability to talk credibly with domain stakeholders clinicians, underwriters, analysts, compliance leads — and hold your own in a design conversation with them.

Nice to have

• Model risk management / model governance experience (SR 11-7 or equivalent).
• Healthcare data standards in practice: FHIR, HL7v2, X12 EDI, ICD/CPT/SNOMED coding.
• Financial data in practice: market data feeds, ledger and reconciliation systems, FIX, ISO 20022.
• SOC 2 Type II or HITRUST audit participation.
• Prior consulting or client-facing delivery in a regulated environment.