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Senior Infrastructure Engineer
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Added 41 mins ago
Forward Deployed Engineer
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Bridgewater, NJ
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…
Added 41 mins ago
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Bausch + Lomb

Forward Deployed Engineer

Bridgewater, NJ, United States

For U.S. locations that require disclosure of compensation, the starting pay for this role is between $170,000.00 and $200,000.00.

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Job details

Pay: For U.S. locations that require disclosure of compensation, the starting pay for this role is between $170,000.00 and $200,000.00.
Posting language: English
Posted: Oct 9, 2026

Original job description

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 outcomesnot 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, solution implementation, or digital transformation, with a strong record of shipping production-quality solutions.
Proficiency in Python and modern API and integration development, with experience building on cloud platforms such as Microsoft Azure or Google Cloud.
Hands-on experience with generative AI, agents, machine learning, and workflow automation in production environments.
Demonstrated experience deploying enterprise technology directly with business users and driving sustained adoption.
Ability to collaborate with and influence cross-functional teams while remaining a hands-on technical contributor.
Strong analytical, troubleshooting, communication, and stakeholder-management skills, with the ability to translate between business needs and technical requirements.

Preferred qualifications

Experience delivering technology solutions across multiple business divisions or corporate functions in a complex global organization.
Experience in pharmaceutical, medical device, healthcare, or another regulated industry.
Experience with Microsoft Copilot, Azure AI services, Claude, or other enterprise AI platforms.
Experience with data platforms such as Snowflake, Microsoft Fabric, OneLake, or similar, and with validated-system or controlled enterprise environments.
Experience supporting large-scale digital transformation, change, or enterprise adoption programs.

This position may be available in the following location(s): Bridgewater, NJ - Hybrid

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 $170,000.00 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.

Job Applicants should be aware of job offer scams perpetrated through the use of the Internet and social media platforms.

To learn more please read Bausch + Lomb's Job Offer Fraud Statement (https://performancemanager.successfactors.eu/doc/custom/BauschLomb/Bausch_job_posting_statement.docx)

Our US Benefit Programs Employee Benefits: Bausch + Lomb (https://www.bausch.com/careers/benefits/)

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.

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More about this job

Skills

Stakeholder management
Change management
Machine learning
Workflow
Regulatory compliance
Documentation
Leadership
Collaboration
Computer science
Python
Microsoft Azure
Google Cloud
Troubleshooting
Communication skills
Snowflake

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