Lead AI Engineer, Agentic AI Solutions

Bausch+Lomb; Bridgewater Township (NJ); Hybride; USD 150 000 - 200 000; Plein temps

Avantages offerts par ce poste

Hybrid work schedule (up to 2 days WFH

Medical, dental, vision benefits

401(k) with company match

Tuition reimbursement

Paid vacation & sick time

Résumé du poste

Bausch + Lomb is seeking a Lead AI Engineer, Agentic AI Solutions, to design and deploy AI-powered tools that support commercial decision-making across brand strategy, customer engagement, market access, and analytics.

The role combines AI engineering with business collaboration to deliver enterprise-scale solutions using modern AI tech, cloud platforms, and large-scale data ecosystems. Hybrid work in Bridgewater, NJ is available with strong governance and compliance expectations.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Engineering, or a 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 with the ability 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 a focus on governance, compliance, and auditability.
• 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, with the ability to translate complex technical concepts for non-technical audiences.

Responsabilités

• Design, build, and operate production Applied agents across the commercial process - 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) segment, returning sourced, reproducible narratives to brand and insights teams.
• Build pre-call, post-call, and next-best-action / next-best-engagement agents that assemble ECP briefs from Glimpse (Next Best Action) platform / CRM attach explainable reasoning to every recommendation and write structured data back to CRM.
• Build measurement and feedback agents supporting 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 rather than corrected afterward.
• Implement determinism and reproducibility controls, including validate-then-lock specification patterns, so any number that drives a targeting, content, or investment decision returns the same result across runs and is fully auditable.
• Integrate agents with enterprise systems; 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 evaluation harnesses per agent, including golden datasets, calibrated LLM-as-judge scoring, and regression testing, and track agent KPIs covering task completion, grounding, reproducibility, human-override rate, latency, and cost per task.

Connaissances

Python

LangChain

LangGraph

CrewAI

AutoGen

LlamaIndex

SQL

Data modeling

APIs

AWS

MLOps

Formation

Bachelor’s or Master’s degree in CS/AI/Engineering

Outils

LangChain

LangGraph

CrewAI

AutoGen

LlamaIndex

Description du poste

Date: Oct 22, 2026

Location: US-NJ-Bridgewater, US

Bausch + Lomb (NYSE/TSX: BLCO) is a leading global eye health company dedicated to protecting and enhancing the gift of sight for millions of people around the world—from the moment of birth through every phase of life. Our mission is simple, yet powerful: helping you see better, to live better.

Our comprehensive portfolio of over 400 products is fully integrated and built to serve our customers across the full spectrum of their eye health needs throughout their lives. Our iconic brand is built on the deep trust and loyalty of our customers established over our 170-year history. We have a significant global research, development, manufacturing and commercial footprint of approximately 13,000 employees and a presence in approximately 100 countries, extending our reach to billions of potential customers across the globe. We have long been associated with many of the most significant advances in eye health, and we believe we are well positioned to continue leading the advancement of eye health in the future.

Overview

The Lead AI Engineer, Agentic AI Solutions will design, build, and deploy AI-powered solutions that support commercial decision-making across brand strategy, customer engagement, market access, and analytics. This highly technical individual contributor role combines AI engineering, software development, and business collaboration to create intelligent systems that drive measurable business outcomes while meeting enterprise standards for governance, reliability, and compliance. You will help shape the future of AI within a global healthcare organization, building enterprise-scale solutions that directly influence business decisions and customer engagement while working with modern AI technologies, cloud platforms, and large-scale data ecosystems.

Key Responsibilities

• Design, build, and operate production Applied agents across the commercial process - 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) segment, returning sourced, reproducible narratives to brand and insights teams.
• Build pre-call, post-call, and next-best-action / next-best-engagement agents that assemble ECP briefs from Glimpse (Next Best Action) platform / CRM attach explainable reasoning to every recommendation and write structured data back to CRM.
• Build measurement and feedback agents supporting 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 rather than corrected afterward.
• Implement determinism and reproducibility controls, including validate-then-lock specification patterns, so any number that drives a targeting, content, or investment decision returns the same result across runs and is fully auditable.
• Integrate agents with enterprise systems; 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 evaluation harnesses per agent, including golden datasets, calibrated LLM-as-judge scoring, and regression testing, and track agent KPIs covering task completion, grounding, reproducibility, human-override rate, latency, and cost per task.
• Design for bounded autonomy: 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 including 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 bring Responsible AI standards into the design phase rather than treating them as a final gate.
• Partner directly with brand teams, field operations, market access, and commercial analytics to translate business asks into agent specifications tied to a defined decision, and to decline use cases where an agent is the wrong tool.
• Participating 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.

Technology Environment

Python • Azure/AWS • Databricks & Snowflake • LLMs & Agentic AI • RAG & Vector Databases • Salesforce/Veeva

Qualifications

Required:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Engineering, or a 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 with the ability 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 a focus on governance, compliance, and auditability.
• 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, with the ability to translate complex technical concepts for non-technical audiences.

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.

Note: This role is eligible for our hybrid work schedule allowing for up to 2 days/week of telecommuting from home and 3 days/week in our Bridgewater, NJ corporate office.

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 $150,000.00 and $200,000.00. 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.

Our US Benefit Programs Employee Benefits: Bausch + Lomb

Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.