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Jobs · Engineering · New Jersey

Head of Enterprise AI Solutions

Bausch + Lomb · Bridgewater, NJ · 2 days ago
Engineering$190k–$220k/yrFull-time

Position Summary

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.

Key Responsibilities

  • 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.

  • 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.

Requirements

  • 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.

Preferred Experience

  • 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.

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