Context Trainer (Developer)

By clicking the Apply button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda's Privacy Notice and Terms of Use. I further attest that all information I submit in my employment application is true to the best of my knowledge. Job Description: THE OPPORTUNITY Curate and govern the context layer (RAG/KBs, embeddings, metadata, labeling) to improve answer quality and minimize hallucinations, while protecting data/PII. Responsibilities Curation & Labeling: Extract and curate content from enterprise sources (Confluence, Jira, SharePoint, ServiceNow, qTest) using APIs and automation. Define chunking and metadata schemas; labeling guidelines; golden Q&A and evaluation sets. Implement chunking strategies for diverse content types (code repositories, technical documentation, tickets, test cases). Implement curation workflows and retention policies. Retrieval Quality: Run A/B experiments across vector stores; monitor answer quality vs. cost/latency; recommend defaults. Analyze failure cases and propose data-driven improvements. Data Governance: Enforce data minimization, retention, and access controls; maintain lineage and approvals per RAI (Responsible AI). Document data sources and usage for audit readiness. Skills & Qualifications Required: 3+ years data/ML experience with embeddings/retrieval expertise; strong documentation and runbook skills. Experience with content transformation, metadata extraction, and labeling workflows. Familiarity with privacy and data governance principles. Hands-on experience with vector stores (OpenSearch/pgvector/Kendra/Chroma) and labeling tools. Experience with REST APIs and data extraction from enterprise systems. Python coding proficiency for data pipelines and automation. Preferred/Nice to have: Experience designing golden datasets and evaluation pipelines. AWS Bedrock Knowledge Bases experience. Familiarity with software development lifecycle and technical documentation patterns. Locations: IND - Bengaluru Worker Type: Employee Worker Sub-Type: Regular Time Type: Full time