Forward Deployed Engineer

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 worldfrom 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.

** Position overview*
* Bausch + Lomb is seeking a Forward Deployed Engineer (FDE) to turn AI from pilots into scalable production capabilities across the enterprise. This is a hands-on builder role embedded within business divisions and corporate functions. You will work directly with teams to understand their needs, develop production-ready AI solutions within real operating environments, and drive sustained adoption and measurable business value.

You will work closely with business leaders, functional subject-matter experts, AI Delivery, Data, and IT to deliver as one team. You will bring strong engineering judgment, translate business challenges into practical solutions, and share reusable approaches that help accelerate AI delivery across Bausch + Lomb.

** How the role works*
* + Hands-on engineering: building, integrating, testing, and hardening solutions to production standards.

+ Focused on process discovery, stakeholder engagement, change management, adoption, and knowledge sharing.

+ Success is measured by adoption, scalability, and business outcomes not by prototypes delivered.

** Key responsibilities*
* Build and deploy

+ Design, code, and deploy AI-enabled solutions, including generative AI, agents, machine learning, and workflow automation, that operate reliably in enterprise environments.

+ Integrate solutions with enterprise applications, data platforms, and business systems through APIs and data pipelines.

+ Own the path from prototype to production: testing, user acceptance, security and compliance review, release, monitoring, and post-deployment support.

+ Apply validation, documentation, data privacy, and risk-management practices appropriate to a regulated global enterprise.

Embed and diagnose

+ Work side by side with business leaders, functional experts, and end users to understand how work is performed and where technology can create value.

+ Assess workflows, identify high-value use cases, and redesign processes around AI rather than layering tools onto legacy steps.

+ Resolve technical, process, and adoption issues quickly in partnership with stakeholders.

Drive adoption and change

+ Treat adoption as a deliverable. Define adoption and value metrics for every deployment and track them after go-live.

+ Build training materials, user guides, and deployment playbooks. Facilitate workshops and train end users.

+ Identify and develop local champions within each function.

+ Capture user feedback and deployment learnings and feed them to the Enterprise AI team to shape product priorities.

Scale capabilities across the enterprise

+ Contribute to technical standards for code quality, deployment, documentation, security, and responsible AI.

+ Partner with business owners and AI leadership to prioritize high-value opportunities across divisions and functions.

+ Build reusable assets, including patterns, templates, connectors, and playbooks, so each deployment makes the next one faster.

+ Share knowledge and mentor colleagues through technical reviews, communities of practice, and hands-on collaboration.

Collaborate across the enterprise

+ Partner with AI Delivery, Data, and IT on architecture, data access, security, and platform standards.

+ Escalate platform gaps and reuse enterprise components instead of building one-off solutions.

** Qualifications*
* + Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent practical experience.

+ Relevant experience in software engineering,…