B
Lead AI Engineer, Agentic AI Solutions
Bausch+Lomb Companies Inc.
5 hours ago
Full-time
On-site
Bridgewater, New Jersey, United States
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.
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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.
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