Sr Software Engineer - Syncade Developer

Bristol Myers Squibb; Hyderabad; On-site; INR 3,500,000 - 6,000,000; Full time

Job summary

Bristol Myers Squibb is seeking a Sr. Software Engineer - AI Engineer to design and operate production-grade AI services integrated with MES systems.

You will own the AI retrieval stack, evaluation, and governance while leading full-stack development of React/TypeScript front ends and Python/Java back ends. The role emphasizes scalable, compliant AI with strong observability, CI/CD and enterprise-grade data architecture.

Qualifications

• 10–12 years of software engineering experience.
• 5+ years building and operating web applications.
• 2+ years delivering AI/ML or GenAI capabilities into production.

Responsibilities

• Design, build and operate production-grade AI services with integration to MES systems.
• Own retrieval architecture, vector storage and LLM patterns with governance.
• Establish AI evaluation, observability and CI gates with robust traceability.
• Lead full-stack development of React/TypeScript front ends and Python/Java back ends.
• Mentor engineers, drive clean code and agile practices across teams.

Skills

AI/ML in production

Web application development

Data modeling

Mentoring / leadership

Education

Bachelor's degree in Computer Science or related field

Master's degree in Computer Science or related field

Tools

PostgreSQL

Oracle/SQL Server

Docker

Kubernetes

OpenTelemetry / observability tooling

Job description

Job Summary

Position: Sr. Software Engineer - AI Engineer

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.
• Build backend services in Python (FastAPI) and/or Java (Spring Boot) exposing REST and GraphQL APIs with OpenAPI-first contracts, secured with OAuth 2.0/OIDC, JWT, SSO and fine-grained RBAC, and write the data access layer with the same rigour as the API (deliberate query design, sound ORM boundaries, pagination, no N+1 access, idempotent writes).
• Implement real-time and AI-assisted experiences - WebSockets/SSE for live batch and equipment status, token streaming with inline citations - alongside validation-rich workflows including e-signature interaction patterns.
• Own quality and performance end to end: automated tests across the stack (pytest, Jest/Vitest, Playwright), load testing, and CI/CD (GitHub Actions, Jenkins, ArgoCD) with GitOps delivery of application and database changes together against measured p95 targets.

System and Data Architecture

• Lead the design of distributed, multi-tenant systems: bounded contexts and Domain-Driven Design, service decomposition, API and event contracts, and evolution strategy. Own the data model end to end - conceptual, logical and physical design, deliberate normalization, and referential integrity, constraints and domain invariants enforced in the database rather than only in application code.
• Demonstrate advanced relational expertise: complex SQL, window functions, CTEs, stored procedures (PL/pgSQL, PL/SQL), partitioning, deliberate indexing strategy, and performance diagnosis from execution plans, statistics, lock contention and pool exhaustion.
• Apply correct transaction design (isolation levels, concurrency control, idempotency, retry semantics) and migration discipline (Flyway/Liquibase/Alembic, expand-contract zero-downtime rollout, tested rollback), and run databases as production assets on AWS: RDS/Aurora PostgreSQL, Multi-AZ, read replicas, pooling, PITR and DR.
• Design regulated-grade data integrity - immutable, append-only audit trails (including hash-chained designs), e-signature records, ALCOA+, retention and archival - satisfying GxP, 21 CFR Part 11 and GAMP 5 (2nd edition, incl. AI/ML guidance) by design, not documentation alone.
• Design event-driven systems with Kafka (partitioning and ordering guarantees, transactional outbox, CQRS and event sourcing, sagas) and enable analytics without burdening the transactional system through change data capture (Debezium) and dimensional models for batch reporting.
• Reason rigorously about non-functional requirements - capacity, scalability, SLOs, failure modes, circuit breakers, backpressure, graceful degradation when a site link is down - and define caching, queuing and throttling strategy (Redis, SQS/SNS, idempotency keys).
• Architect for hybrid deployment (on-premise and near-line where shop-floor latency demands it, AWS for scale) using Docker, Kubernetes (EKS/ECS) and IaC; instrument for observability (Prometheus, Grafana, OpenTelemetry); and apply security by design, mitigating the OWASP Top 10 and OWASP Top 10 for LLM Applications.

Collaboration and Leadership

• Partner with Manufacturing, MST, Quality, Automation and site IT to translate process needs into system and data design; produce and defend the artifacts of real architecture work (ADRs, design documents, data models, sequence and data-flow diagrams, threat models) and run design reviews; and communicate integration contracts to technical and non-technical stakeholders.
• Mentor engineers, review code and designs, and raise the bar on clean code, TDD/BDD and craftsmanship - including governed AI-assisted development that improves throughput without weakening review rigour or compliance - while driving continuous improvement through Agile/Scrum across global teams.

Required Qualifications Skills

• Bachelor s or Master s degree in Computer Science, Software Engineering or a related field, with 10-12 years of software engineering experience, including 5+ years building and operating web applications and 2+ years delivering AI/ML or GenAI capabilities into production (prototypes alone will not qualify).
• Expert-level SQL and relational data modeling with deep hands-on PostgreSQL (or Oracle/SQL Server): schema design, indexing, query tuning, transactions and migrations.

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