Senior Software Engineer - Syncade Developer

At Bristol Myers Squibb, our employees often ask, “Who are you working for?”—a question that fuels collaboration, accountability, and urgency in our work. Our purpose-driven culture inspires us to discover, develop, and deliver innovative medicines to prevail over serious diseases. We offer uniquely interesting and meaningful work, opportunities for growth, and a supportive environment that values inclusion, wellbeing, flexibility, and comprehensive benefits. This is work that transforms the lives of patients, and the careers of those who do it. Position: Sr. Software Engineer – AI Engineer At Bristol Myers Squibb, we are inspired by a single vision – transforming patients’ lives through science. Each of our colleagues contribute to innovations that drive meaningful change. Scope The EMES core platform, its components, interfaces, data layer and tools – Material and Inventory, Order Management, Equipment and Instrument Integration, Sample Management, Patient Scheduling System integration, Label Printing, Recipe Authoring and Execution, Electronic Batch Records, and Batch Reporting and Analytics – together with: AI and GenAI services embedded in manufacturing workflows: assistants, retrieval over controlled documents, anomaly detection and decision support. Web applications and operator-facing interfaces across shop-floor, quality and supply-chain personas. Enterprise data models, databases, audit-trail architecture and reporting data flows; cloud migration and adoption of next-generation manufacturing systems. Key Responsibilities AI Engineering Design, build and operate production-grade AI services – not prototypes – including retrieval-augmented generation over SOPs, batch records, deviations and equipment documentation, and agentic workflows that act against MES systems under human oversight. Own the retrieval architecture (chunking, embedding selection, vector storage such as pgvector or OpenSearch, hybrid search, re-ranking, citation fidelity) and LLM application patterns: structured output and tool calling, MCP servers over enterprise systems, orchestration, cost controls and guardrails. Establish AI evaluation and observability: golden datasets, offline and online evals, regression gates in CI, hallucination and drift detection, tracing and human-in-the-loop review. Apply classical ML where it is the better tool (anomaly detection, forecasting, predictive quality) and ensure responsible, compliant AI: data classification, IP and PII protection, model and prompt versioning, reproducibility and validation evidence for GxP-relevant use. Web Application Development Deliver full-stack applications: React with TypeScript front ends, component libraries and design systems, and responsive, accessible (WCAG) interfaces built for gloved, time-pressured shop-floor use as well as office users.