Director of AI & Data Engineering

Petra Funds Group • New York, NY

2d • $146,000 - $219,000 • Hybrid

About The Position

The Director of AI & Data Engineering will be responsible for establishing Petra’s AI operating model and governance by leading internal stakeholders and external vendors. Acts as Petra’s internal product owner for AI, ensuring solutions are secure, auditable, and operationally reliable in a regulated environment.

Requirements

• Degree in Computer Science, Data Science, Engineering, Statistics or equivalent. Master’s/PhD desirable but not required.
• 5+ years professional experience in data science/data engineering/ML engineering with 3+ years building production ML/AI systems.
• Hands-on with LLMs and retrieval-augmented pipelines (RAG): prompt engineering, fine-tuning/adapter workflows, embeddings, and vector databases
• Demonstrated experience building, deploying, and maintaining production-grade software in Python, Java, C++, TypeScript/JavaScript, or similar languages.
• Strong stakeholder management: ability to run discovery workshops, create business cases, and translate requirements into technical scope.
• Excellent communication skills for non-technical audiences; proven track record of operational handover and training.

Responsibilities

• Own Petra’s AI strategy for cross-functional operational improvement: maintain a 12–18 month AI roadmap aligned to Petra’s business priorities and budget.
• Lead build vs. buy evaluations, vendor selection and contracting for AI platforms and services; manage external partners and strategic design vendors.
• Run structured discovery workshops with Fund Accounting, Compliance, Investor Services, Credit, Management Company and other teams to surface and scope AI use cases.
• Prioritize by expected value, implementation complexity, data readiness, regulatory risk, and required budget/resources; maintain an upfront ROI / FTE-savings model for each case.
• Build and maintain a use-case backlog with clearly defined acceptance criteria and success metrics.
• Own delivery from prototype to internal production by leading vendors and internal stakeholders; remain hands-on enough to validate architecture, review outputs, and enforce engineering standards (prototypes → UAT → production).
• Implement MLOps/AIops best practices: automated testing, CI/CD for models and code, model monitoring (accuracy, drift), logging, cost monitoring and rollback procedures.
• Establish release discipline for rules, prompts, and code: PR review expectations, UAT gating, regression test harness, approval workflow, and rollback procedures.
• Define reliability targets for daily operational use (latency, uptime, error handling) and implement monitoring/alerting, runbooks, and incident response ownership (vendor vs internal).
• Ensure outputs meet deterministic auditability and explainability standards where required (e.g., financial statement QC, rule-catalog based audits). Adopt strong templates such as requirements→rule catalog→prototype→validation→handoff.
• Own integration with Petra systems (Office365/SharePoint, Allvue / FIS VPM and similar portfolio systems, document stores, Fund Accounting platform). Design secure connectors, data pipelines, and SSOT (single source of truth) data models.
• Design and enforce AI governance: data privacy, access control, SOC2/17a-4 readiness, model usage limits, PII handling, vendor risk assessment, and contractual terms.
• Coordinate legal, compliance and security reviews; ensure contractual restrictions with model hosts and clear IP/usage rights.
• Create training, documentation, and handover packages for operational teams. Run super-user programs and adoption campaigns. Consultant engagements strongly emphasize transfer and handover to internal teams — replicate this as a core deliverable.
• Build repeatable templates and playbooks for future AI rollouts (intake → requirements → validation → rollout → support), including documentation sufficient for audit and operational handoff.
• Define and report KPIs: FTE hours saved, accuracy/coverage of automated checks, cycle-time reductions, user adoption, cost of ownership, and revenue or margin impacts for value-creating products.
• Deliver quarterly business-impact reports tied to Petra’s strategic goals.
• Act as senior technical peer/mentor to Petra’s engineering and data teams: code reviews, architecture guidance, hands-on contributions to data engineering and analytics projects where needed.

Benefits

• 90% covered medical, dental, and vision insurance premiums to help you stay healthy without financial strain.
• Fully funded Health Savings Account (HSA) employer contributions up to the IRS maximum — available to employees enrolled in our high-deductible health plan.
• 401(k) employer match at 100% of your contributions up to 5% of compensation, with immediate vesting, so you start building long-term savings right away.
• Flexible paid time off to recharge, travel, or take care of what matters most.
• Generous holiday calendar to ensure you have time to rest, reflect, and celebrate throughout the year.
• Hybrid work environment that offers flexibility and supports work-life balance.

What This Job Offers

• Job Type: Full-time
• Career Level: Director