Job Description

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 Summary

We are seeking a curious, hands-on engineer to join our Global Sales Systems and Capabilities team within CBI&T (Commercial Business Insights & Technology) in Hyderabad. This role is focused on building AI-powered capabilities for our field force on Veeva Vault CRM – from LLM-based assistants and agentic workflows to the data pipelines and integrations that ground them in trusted commercial data. The ideal candidate has 2–4 years of experience in software or data engineering with Python, SQL and AWS, and at least 1 year of hands-on experience taking LLM/GenAI features from prototype to production. This is an applied AI engineering role – deep ML research or model-training experience is not required; what matters most is a builder with a product mindset who cares whether what they ship is used and trusted by field users. If you want an exciting and rewarding career that is meaningful, consider joining our diverse team!

Key Responsibilities

• Design, build and ship AI/LLM-powered features for Vault CRM field users – such as pre-call insights, call note summarization, conversational assistants and next-best-action recommendations – using prompt engineering, retrieval-augmented generation (RAG), tool/function calling and agentic workflows.
• Build and maintain the data foundation for AI: cloud-based (AWS) batch and event-driven pipelines (Glue, Lambda, API Gateway, EventBridge) and integrations with Vault CRM (e.g., Vault REST APIs, Direct Data API) and related commercial systems that supply clean, timely and governed context to AI applications.
• Implement retrieval components – document ingestion, chunking, embeddings, vector/hybrid search and metadata filtering – and tune them for relevance and accuracy.
• Integrate foundation models through enterprise platforms (e.g., Amazon Bedrock, Anthropic, Azure OpenAI) and expose AI capabilities through secure APIs, Model Context Protocol (MCP) servers and/or native Vault CRM extensions.
• Make evaluation part of the build: create test datasets, define quality metrics (accuracy, groundedness, hallucination rate) and run automated and human-in-the-loop evaluations before and after each release.
• Monitor AI applications in production – tracing, latency, token cost and user feedback – and continuously improve prompts, retrieval and model choices based on what the data shows.
• Apply responsible AI guardrails appropriate for a regulated life sciences environment, including PII handling, content safety, access controls and commercial compliance considerations, in partnership with security, privacy and AI governance teams.
• Bring a product mindset: partner with field users, business stakeholders and product managers to understand workflows, shape use cases, build quick prototypes to validate value, and define success measures such as adoption, time saved and user satisfaction.
• Stay current with fast-evolving AI tools and practices, use AI-assisted development tools effectively, and share learnings with the broader Field Integrations team to raise AI fluency across the group.
• Participate in effort estimation, code reviews, CI/CD and production support, and maintain standard technical documentation such as design documents, deployment checklists and testing/validation records.

Qualifications & Experience

• Bachelor’s degree in Computer Science, Information Technology, or related field.
• 2–4 years of IT experience in software development or data engineering, including at least 1 year of hands-on experience building LLM/GenAI applications (production experience preferred; strong project or POC work will be considered).
• Strong programming skills in Python, with sound engineering practices – clean code, testing, version control (Git) and CI/CD.
• Good SQL skills and understanding of relational databases (preferably PostgreSQL); experience building and consuming RESTful APIs.
• Hands-on experience with AWS services such as Lambda, API Gateway, Glue, S3 and EventBridge.
• Practical experience with LLM APIs and at least one orchestration/agent framework (e.g., LangChain/LangGraph, LlamaIndex, Strands Agents, Bedrock Agents), including prompt engineering, structured outputs and tool/function calling.
• Understanding of RAG architecture, embeddings and vector stores (e.g., OpenSearch, pgvector).
• Familiarity with LLM evaluation and observability approaches and awareness of common failure modes such as hallucination, prompt injection and data leakage.
• Product mindset – ability to turn an ambiguous business problem into a well-scoped AI solution, explain trade-offs (quality, latency, cost) clearly to non-technical stakeholders, and iterate based on user feedback.
• Ability and willingness to learn new technologies quickly; proactive and self-motivated, with a strong sense of ownership and accountability.

Good to Have

• Experience with Veeva Vault CRM or Veeva CRM (Salesforce-based), Vault APIs, or other CRM platforms.
• Life sciences / pharma commercial domain knowledge (field force effectiveness, HCP engagement, compliance).
• Exposure to MCP, multi-agent patterns, or speech-to-text/voice AI use cases.
• Ability to build lightweight front-ends for AI prototypes (e.g., React).
• Experience with Docker and infrastructure-as-code (Terraform, CloudFormation or AWS CDK).
• AWS or GenAI certifications

We hire for skills and capabilities, not just credentials – if this role excites you, but doesn’t perfectly match your resume, we encourage you to apply anyway.

How We Work

Where you work matters – because collaboration, innovation and patient impact happen in many settings. Our roles are structured across four work models: site-essential, site-by-design, field-based and remote-by-design. The model assigned to this role is based on its core responsibilities. Learn more at https://careers.bms.com/ways-of-working.

Supporting People with Disabilities

BMS is dedicated to ensuring that people with disabilities can excel through a transparent recruitment process, reasonable workplace accommodations/adjustments and ongoing support in their roles. Applicants can request a reasonable workplace accommodation/adjustment prior to accepting a job offer. If you require reasonable accommodations/adjustments in completing this application, or in any part of the recruitment process, direct your inquiries to adastaffingsupport@bms.com. Visit careers.bms.com/eeo-accessibility to access our complete Equal Employment Opportunity statement.

Candidate Rights

BMS will consider qualified applicants with arrest and conviction records, pursuant to applicable laws in your area.

For roles based in Los Angeles County only: If you live in or expect to work from Los Angeles County if hired for this position, please visit this page for important additional information: https://careers.bms.com/california-residents/

For roles based in Washington State only: If you live in or expect to work from Washington State if hired for this position, please visit this page for important information about the Washington Fair Chance Act.

Data Protection

We will never request payments, financial information, or social security numbers during our application or recruitment process. Learn more about protecting yourself at https://careers.bms.com/fraud-protection.

Any data processed in connection with role applications will be treated in accordance with applicable data privacy policies and regulations.

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R1608217 : Field AI Engineer