Head Of Model Risk Management Jobs in Fairhaven, MA

Location: US-NJ-Bridgewater, US

The Head of Enterprise AI Solutions is a leader responsible for owning the Enterprise AI product portfolio end to end, including AI product strategy, delivery, governance, and responsible deployment at scale.

This is a hands‑on leadership role combining technical depth, product ownership, and people leadership. The Head of Enterprise AI Solutions builds and leads a team of AI engineers and product-oriented practitioners while remaining actively involved in designing, building, and shipping AI products, particularly AI agents that reason, use tools, and execute end-to-end business workflows.

Success in this role is measured by AI solutions or products delivered and adopted, business outcomes achieved, and the establishment of a trusted, scalable AI governance framework that enables innovation while managing risk.

• Own the enterprise AI solutions strategy and roadmap, aligning AI investments to strategic business priorities.
• Reimagine enterprise workflows with an AI first product mindset, identifying and prioritizing high value opportunities for AI driven transformation.
• Partner with executive and business leaders to frame ambiguous problems, quantify value, and translate opportunities into clear AI solution hypotheses.
• Define and own product KPIs for each AI product; track adoption, usage, and business impact post-launch, reporting outcomes to executive stakeholders.
• Drive product/solution discovery and validation through user research, prototyping, and structured experimentation before committing to full-scale build.
• Embed MVP discipline into AI solution delivery scope minimum viable releases, gather user feedback early, and iterate based on observed outcomes.
• Serve as the voice of the internal customer, maintaining continuous feedback loops with business users to inform backlog priorities and solution direction.
• Provide dotted-line leadership to AI Agent Builders embedded within business functions, ensuring alignment to enterprise AI standards, architecture, governance, and delivery practices.
• Define and maintain the operating model for how function-embedded Agent Builders collaborate with the central AI Solutions team including shared tooling, code standards, model selection guidelines, reusable components, and escalation paths.
• Partner with functional leaders to scope Agent Builder roles, support hiring and onboarding, and ensure embedded talent is equipped to build and deploy AI agents that meet enterprise-grade quality and compliance requirements.
• Own and lead AI governance across the enterprise, including policies, standards, guardrails, and operating models.
• Establish and enforce Responsible AI practices, including model risk management, human-in-the-loop design, escalation paths, monitoring, and auditability, with specific attention to regulatory requirements in the pharmaceutical and MedTech space (e.g., FDA, HIPAA, GxP, and applicable data privacy regulations).
• Remain actively hands on in designing and building AI products and agent based solutions.
• Build and review AI agents using Python, LLM APIs, and modern agent frameworks that analyze information, call tools/APIs, and complete tasks end to end.
• Ensure production ready delivery using enterprise AI platforms (e.g., Azure AI services), with strong security, observability, and reliability.
• Build, lead, and develop a high performing AI Solutions team.
• Foster a culture of product ownership, build first execution, and accountability.
• Operate within Agile product delivery models, managing backlogs, iterative releases, and outcome-based prioritization.
• Balance speed of innovation with enterprise grade quality, governance, and operational stability.
• Lead AI product or solution delivery within Agile frameworks, including ownership of product backlogs, sprint planning, backlog refinement, release planning, and sprint retrospectives.
• Accountable for iterative, outcome-based delivery — managing scope, schedule, and quality across concurrent AI product workstreams.
• Track team-level delivery metrics (velocity, cycle time, release cadence) and drive continuous improvement in execution.

• Bachelor’s degree in Engineering, Computer Science, Information Systems, Business, or a related field; advanced degree preferred.
• 8+ years of experience in software engineering, AI/ML, automation, or digital product delivery in enterprise environments.
• 3+ years of hands‑on experience building and deploying AI products, including LLM based systems.
• Demonstrated experience leading technical and product teams and delivering complex solutions at scale.
• Strong ability to translate ambiguous business needs into shippable AI products.
• Excellent executive communication skills and ability to influence across functions.

• Experience owning AI governance frameworks (Responsible AI, model risk, security, compliance).
• Deep familiarity with enterprise AI platforms (e.g., Azure AI services, Foundry style platforms).
• Experience with multi model / model garden approaches, selecting models based on quality, cost, latency, and risk.
• Experience operating in regulated, complex, or global enterprises.
• Background blending product leadership, consulting style problem solving, and hands on engineering.
• 5+ years of experience operating in the pharmaceutical, MedTech, consumer health, or life sciences industry strongly preferred.
• Strong understanding of AI agent architectures, orchestration, tool calling, and human in the loop design.

This position may be available in the following location(s): US - Bridgewater, NJ

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.

For U.S. locations that require disclosure of compensation, the starting pay for this role is between $190,000.00 and $220,000.00. The estimated salary range reflects an anticipated range for this position. The actual base salary offered may depend on a variety of factors.

U.S. based employees may be eligible for short-term and/or long-term incentives. They may also be eligible to participate in medical, dental, vision insurance, disability and life insurance, a 401(k) plan and company match, a tuition reimbursement program (select degrees), company holidays, and well-being benefits, among others. U.S. based employees are also eligible to receive sick time, floating holidays and paid vacation.