Bausch+Lomb Companies Inc. is seeking a Lead AI Engineer to design, build, and deploy agentic AI solutions that support commercial decision-making. This hybrid role is based in Bridgewater, NJ, with the ability to work up to 2 days per week remotely and 3 days per week from the corporate office.
The Lead AI Engineer will combine AI engineering with production software development to deliver governed, auditable enterprise systems. The work focuses on production-grade agents that support brand strategy, customer engagement, market access, and analytics, with deterministic behavior and evaluation rigor built into the platform.
Responsibilities
- Design, build, and operate production Applied agents across the commercial process, including brand strategy, customer insights, personalized engagement, and closed-loop feedback, composing foundational agents rather than rebuilding them.
- Build performance investigation agents that autonomously decompose brand performance shifts across geography, channel, payer, and Eye Care Professional (ECP) segments, returning sourced and reproducible narratives for brand and insights teams.
- Create pre-call, post-call, and next-best-action / next-best-engagement agents that assemble ECP briefs from Glimpse (Next Best Action) platform / CRM, explainable reasoning for each recommendation, and structured data writes back to the CRM.
- Develop measurement and feedback agents to support A/B and multivariate test design, readout, and write-back into the planning loop.
- Ground all agents in the enterprise semantic layer and commercial knowledge graph so metric definitions, joins, grain, and row- and role-level access are resolved before query generation.
- Implement determinism and reproducibility controls, including validate-then-lock specification patterns, to ensure decision-driving numbers remain consistent across runs and fully auditable.
- Integrate agents with enterprise systems including Glimpse (NBA platform) /Veeva or Salesforce, Adobe, and internal commercial platforms using Model Context Protocol (MCP), agent-to-agent (A2A) patterns, tool discovery, scoped authentication, and structured outputs.
- Build and maintain agent evaluation harnesses using golden datasets, calibrated LLM-as-judge scoring, regression testing, and KPI tracking (task completion, grounding, reproducibility, human-override rate, latency, and cost per task).
- Design for bounded autonomy where agents prepare, propose, investigate, summarize, and route, while humans in loop approve claims, privacy-sensitive actions, and validated-record changes.
- Operate agents in production, owning observability and tracing, Evals, token and cost controls (loop caps, model routing and fallback, latency budgets), versioning, rollback, on-call response, and postmortems.
- Partner with Medical, Legal, Regulatory, Privacy, Compliance, and IT to incorporate Responsible AI standards during design.
- Collaborate directly with brand teams, field operations, market access, and commercial analytics to translate business requests into agent specifications tied to a defined decision, and decline use cases where an agent is the wrong tool.
- Participate in Agile AI Operations, including backlog management, sprint planning, cross-functional collaboration, and continuous improvement.
- Contribute reusable patterns, components, and documentation to the shared agent pattern library, and mentor engineers and analysts adopting them.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Engineering, or related field.
- 5+ years of experience building and deploying production software, AI, or ML solutions, including LLM-powered applications.
- Strong Python development skills and software engineering best practices, including testing, CI/CD, APIs, code reviews, and containerization.
- Hands-on experience with AI agent frameworks such as LangChain, LangGraph, CrewAI, AutoGen, LlamaIndex, or similar.
- Experience with tool calling, structured outputs, function schemas, and enterprise system integrations.
- Experience designing and implementing RAG solutions, vector databases, embeddings, and retrieval systems.
- Strong SQL and data modeling skills to define and validate business metrics.
- Experience developing frameworks and metrics to evaluate AI/LLM performance.
- Experience with cloud and MLOps platforms such as AWS, Azure, Databricks, Snowflake, and orchestration tools.
- Experience operating in regulated environments with governance, compliance, and auditability focus.
- Proven ability to collaborate effectively across technical and business functions.
- Experience working in Agile environments using Scrum, SAFe, or similar methodologies.
- Strong communication and presentation skills for translating complex technical concepts for non-technical audiences.
Technologies
- Python, Azure, AWS, Databricks, Snowflake
- LLMs, Agentic AI, RAG, vector databases, embeddings, retrieval systems
- Salesforce, Veeva, CRM, Adobe, Glimpse
- LangChain, LangGraph, CrewAI, AutoGen, LlamaIndex
- Model Context Protocol (MCP), A2A patterns, model routing, tool discovery, structured outputs, function schemas
- Knowledge graphs, semantic layer, semantic modeling, containerization
- MLOps, CI/CD, SQL, A/B testing, multivariate testing, Evals
- Scrum, SAFe
Benefits
- Medical, dental, vision insurance
- Disability and life insurance
- 401(k) plan and company match
- Tuition reimbursement program (select degrees)
- Company holidays; well-being benefits
- Sick time; floating holidays; paid vacation
- U.S. based employees may be eligible for short-term and/or long-term incentives
Preferred
- Experience with pharmaceutical, medical device, or consumer health commercial data, including prescription, claims, payer, CRM, and sales data.
- Familiarity with eye care industry dynamics, including ophthalmology, optometry, and Eye Care Professional (ECP) channels.
- Experience with Veeva and/or Salesforce integrations.
- Experience with knowledge graphs, semantic modeling, and semantic layer tools.
- Familiarity with healthcare compliance requirements, including HIPAA, GDPR, FDA promotional regulations, and MLR/PRC review processes.
- Experience with LLM observability, monitoring, and AI cost management.
- Experience working in regulated industries with strong governance, auditability, and compliance requirements.
Salary: USD 150,000 to 200,000 per year. Work authorization: applicants must be authorized to work for any employer in the U.S.; the company is unable to sponsor or take over sponsorship of an employment visa at this time.
Eligible for hybrid work schedule: up to 2 days/week telecommuting and 3 days/week in the Bridgewater, NJ corporate office.
