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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal AI Solutions Engineer - **Company:** Bausch & Lomb Incorporated - **Location:** Bridgewater, NJ, United States - **Salary:** $165,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Microsoft Azure, Information Systems, Statistical Hypothesis Testing, Python (Programming Language), Software Engineering, Systems Integration, Workflow Management Systems, Large Language Models, Multi-Agent Systems, AI Platforms, Information Technology, Data Management - **Published:** July 23, 2026 - **Apply:** https://dejobs.org/x/x/81654D4122CC4B458991485771F17B76/job/ ## About the Role * Bachelors 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., 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. ## Description 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., * 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. ## Related Videos - [Inside the AI Revolution: How Microsoft is Empowering the World to Achieve More](https://www.wearedevelopers.com/videos/869-inside-the-ai-revolution-how-microsoft-is-empowering-the-world-to-achieve-more) - [This App Reached 10,000 Users in One Week. 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