Software Engineering Lead

Job Summary

This role serves as the Software Engineering Lead for Conversational AI within the Commercialization Content Capabilities - HYD team, responsible for architecting and delivering enterprise-grade Conversational AI and Generative AI solutions that support Patients, Healthcare Professionals, and Researchers. The ideal candidate combines deep technical expertise in Agentic AI, Retrieval-Augmented Generation (RAG), and LLM orchestration with a proven ability to lead cross-functional engineering teams in a regulated, compliance-driven environment.

You will lead the design and delivery of low-code chatbot orchestration platforms, compliant RAG-based middleware, and high-availability microservices that power patient support programs and HCP engagement tools on a global scale. This role demands a builders mindset - someone who can architect scalable AI infrastructure, ground LLM responses in approved medical literature, and embed intelligent, MLR-compliant capabilities across the conversational AI lifecycle.

This is a unique opportunity to sit at the intersection of AI innovation, platform engineering, and regulatory compliance, shaping how BMS engages patients, healthcare professionals, and caregivers through its global conversational AI channels.

Key Responsibilities

• Conversational AI & Agentic Platform Leadership: Lead technical strategy and end-to-end engineering for enterprise Conversational AI Platforms, delivering compliant AI solutions for pharmaceutical and healthcare use cases.
• Architect proprietary low-code/no-code chatbot orchestrators leveraging reusable templates, reducing time-to-market for new patient and HCP-facing bots.
• Engineer high availability microservices architecture supporting concurrent global sessions across multiple patient support programs, ensuring 99.9% uptime and seamless scalability.
• Manage and mentor a cross-functional team of engineers and designers, establishing high-performance standards that bridge AI innovation with user experience.
• RAG, LLM & Compliance Engineering: Develop compliant Agentic middleware utilizing RAG and semantic search to ground LLM responses in approved medical literature, eliminating hallucinations in patient-facing interactions.
• Design, train, and fine-tune AI/ML models for conversational use cases, including intent recognition, sentiment analysis, and semantic search over medical content.
• Build intelligent escalation engines with real-time sentiment analysis to detect user friction, enabling seamless hand-off to live agents while capturing insights for continuous model optimization.
• Establish MLR compliance standards, model evaluation benchmarks, and AI governance frameworks for conversational AI deployments.
• Platform, API & Cloud Engineering: Develop and maintain RESTful APIs and backend services supporting AI-powered chatbot functionality, integrating with medical databases and knowledge repositories.
• Build and operationalize AI-powered workflows across cloud ecosystems, integrating with APIs from OpenAI, Azure AI, AWS Bedrock, or similar platforms.
• Implement secure data handling practices ensuring HIPAA compliance and patient data privacy across all AI interactions.
• Evaluate emerging AI tools and frameworks, prototype innovative solutions, and present business cases for adoption.

Qualifications & Experience

• Bachelor's degree in computer science, Information Technology, or related field; 8+ years of experience in Conversational AI, Agentic AI, or Generative AI platform engineering.
• Proven experience architecting RAG-based systems and semantic search solutions with demonstrated MLR or regulatory compliance outcomes.
• Hands-on expertise with LLMs (GPT, Claude, LLaMA), LangChain, Hugging Face, and prompt engineering for enterprise chatbot and virtual assistant use cases.
• Strong proficiency in Python, Node.js, and JavaScript; experience with vector databases (Pinecone, Weaviate) and NoSQL/relational databases (MongoDB, PostgreSQL, Redis).
• Working knowledge of cloud platforms (AWS, Azure) and DevOps tooling (Docker, Kubernetes, CI/CD) supporting high availability microservices.
• Demonstrated ability to lead cross-functional engineering teams in agile environments, with strong stakeholder management and communication skills.
• Familiarity with HIPAA standards, patient-facing solution design, and healthcare/life sciences compliance requirements.