Principal AI Solutions 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 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.

Position Summary

The Principal AI Solutions Engineer is a hands-on individual contributor responsible for designing, building, and deploying production-ready AI solutions, with a strong focus on AI agents that reason, use tools, and complete end-to-end business tasks. The Principal AI Solutions Engineer sits within the AI / Digital Center of Excellence (CoE) and partners across the enterprise to convert real workflows, SOPs, and decision logic into secure, scalable AI-driven solutions.

The Principal AI Solutions Engineer blends deep engineering execution with a consulting mindset. You will work directly with business leaders to frame problems, identify value, and deliver AI agents that measurably improve speed, cost, quality, or cycle time. Success is defined by solutions shipped, adopted, and delivering impact, not slideware. The Principal AI Solutions Engineer has no people management responsibilities and is strongly build-first.

Key Responsibilities

• Re-imagine enterprise work with an AI-first mindset: Diagnose end-to-end processes and identify high-value workflows suitable for AI-driven transformation.
• Process-to-agent translation: Map workflows, SOPs, controls, and decision logic; facilitate working sessions with business SMEs to decompose them into agent-friendly steps (reasoning, execution, validation, escalation, human-in-the-loop).
• Consultative problem framing & value prioritization: Partner with business leaders to structure ambiguous problems, quantify impact, and translate them into clear AI solution hypotheses.
• Build AI agents (hands-on): Develop agents using Python and modern agent frameworks to analyze information, follow procedures, call tools/APIs, and complete tasks end-to-end.
• Integrate with enterprise systems: Build logic layers and integrations across APIs, workflow tools, data platforms, and approved enterprise data sources.
• Deploy securely to production: Use enterprise AI platforms (e.g., Azure AI Foundry) with appropriate security, access controls, monitoring, and reliability practices.
• Production quality & Responsible AI: Implement guardrails, observability, evaluation, and fallback mechanisms to ensure safe and reliable operation.
• Operate in Agile delivery cycles: Manage work through backlogs, iterative releases, and measurable outcomes in close collaboration with IT, data, security, and platform teams.

Requirements

• Bachelor’s degree in business, Engineering, Computer Science, Information Systems, or a related field; advanced degree preferred.
• 5+ years of experience in software engineering, automation, process engineering, or related technical roles delivering production solutions.
• 1+ year hands-on experience building with LLM APIs and/or agent frameworks (not just experimentation, shipping is preferred).
• Experience operating in consulting-style or advisory roles, including problem structuring, executive communication, and influencing without authority.
• Proven ability to translate ambiguous workflows into scalable enterprise solutions.
• Strong communication skills to translate between business needs and technical implementation

Preferred Experience

• Experience deploying solutions using enterprise AI platforms and services (e.g., Azure Foundry AI capabilities and deployment patterns).
• Familiarity with a “model garden” approach (using multiple LLM providers/models through a unified platform) and selecting the right model for task quality, latency, and cost.
• Experience in regulated, complex, or global enterprise environments; comfort operating with security/compliance constraints.
• Background in process transformation, operational excellence, or management consulting style problem solving, including hypothesis-driven analysis and executive-level communication.

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 $165,000.00 and $190,000.00. 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.

Our 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.

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