Lead AI Engineer - Enterprise Agentic AI & Production

Bausch+Lomb Companies Inc.

Bridgewater Township (NJ)

Hybrid

USD 150,000 - 200,000

Full time

3 days ago

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Benefits offered by this job

Medical, dental, vision insurance

Disability and life insurance

401(k) plan and company match

Tuition reimbursement program (select

Job summary

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.

Qualifications

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 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.

Responsibilities

Design, build, and operate production Applied agents across the commercial process, including brand strategy, customer insights, personalized engagement, and closed-loop feedback.
Build performance investigation agents that autonomously decompose brand performance shifts across geography, channel, payer, and ECP segments.
Create pre-call, post-call, and next-best-action / next-best-engagement agents assembling ECP briefs from Glimpse/CRM with explainable reasoning.
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 resolving definitions, joins, grain, and access before query generation.
Implement determinism and reproducibility controls to ensure auditable numbers across runs.
Integrate agents with Glimpse/Veeva/Salesforce, Adobe, and internal platforms using MCP, A2A patterns, and structured outputs.
Build and maintain agent evaluation harnesses with golden datasets, LLM-as-judge scoring, regression testing, and KPI tracking.
Design for bounded autonomy where humans in the loop approve critical actions and validated changes.
Operate agents in production with observability, tracing, Evals, token and cost controls, versioning, and on-call support.
Partner with Medical, Legal, Regulatory, Privacy, Compliance, and IT to apply Responsible AI standards.
Collaborate with brand teams to translate business requests into agent specifications tied to a defined decision.