Data Strategy Innovation Analyst

Job Description Data Strategy Innovation Analyst The Opportunity Based in Hyderabad, join a global healthcare biopharma company and be part of a 130-year legacy of success backed by ethical integrity, forward momentum, and an inspiring mission to achieve new milestones in global healthcare. Be part of an organisation driven by digital technology and data-backed approaches that support a diversified portfolio of prescription medicines, vaccines, and animal health products. Drive innovation and execution excellence. Join a team that is passionate about using data, analytics, and insights to drive decision-making and create custom software, allowing us to tackle some of the worlds greatest health threats. Role Overview Design and implement Automation and Agentic AI systems to support data governance, enablement and stewardship activities. This individual will be responsible for designing the solution using approved architecture patterns, developing orchestration logic, tool use, and memory strategies. This will include developing last mile automation and AI capabilities to enable around data access management and automation Develop production quality code for basic automation, AI agents, services, and supporting infrastructure. Build agents capable of: Executing multi step workflows Interacting with enterprise data, metadata, and knowledge systems Reasoning over policies, standards, and governance rules Escalating decisions or exceptions appropriately Integrate LLM based agents with existing data platforms, governance tools, catalogs, document repositories, and APIs. Apply modern software engineering best practices including modular design, version control, testing automation, observability, and CI/CD pipelines. Deployment, Operations & Scaling Package and deploy AI solutions into development, test, and production environments. Monitor agent behavior, performance, and outputs to ensure reliability, traceability, and policy compliance. Diagnose and remediate failures, hallucinations, workflow breaks, or data quality dependencies. Refactor prototypes into scalable, maintainable production services . Support the expansion of successful agents from team level solutions to company wide platforms . Data Governance & Responsible AI Engineering Engineer guardrails to enforce data governance, privacy, security, and Responsible AI principles . Implement logging, auditing, explainability, and versioning for AI agents and prompts. Ensure solutions comply with regulatory, security, and internal governance requirements. Collaborate with governance and legal partners to operationalize Responsible AI controls in code and architecture. Enablement & Knowledge Management Develop agents that improve knowledge capture, classification, retrieval, and reuse . Produce technical documentation, architecture diagrams, and runbooks for AI solutions. Enable other teams to adopt, extend, or integrate AI agents through reusable patterns and components. What should you have Bachelor s degree in computer science, Software Engineering, Data Science, or equivalent practical experience. Strong hands on software engineering experience , with demonstrated delivery of production systems. 3 Years +Experience developing LLM powered or AI driven applications , including orchestration, prompt engineering, and tool integration. Proficiency in one or more modern programming languages (e.g., Python, TypeScript, Java). Experience working with APIs, microservices, and cloud based architectures. Familiarity with data management, metadata, data quality, governance, or knowledge systems. Ability to move from ambiguous problem statements to implemented, running systems . Preferred Qualifications Direct experience building Agentic AI architectures using frameworks such as LangChain, Semantic Kernel, AutoGen, or similar. Experience with enterprise data catalogs, governance platforms, or knowledge management systems. Cloud deployment experience (e.g., Azure, AWS, or GCP), including security and identity integration. Experience operationalizing AI: monitoring, cost control, reliability, and model lifecycle management. Background in Responsible AI, compliance engineering, or AI risk mitigation. Primary Skills AI & Software Engineering Excellence Agentic Workflow & Systems Design Production Grade Development & Operations Data Governance & Policy Aware Engineering Iterative Delivery & Quick Win Execution Cross Functional Collaboration Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.