Job Description

1.GenAI Development & Integration

- Design and implement GenAI workflows for enterprise use cases.
- Develop prompt engineering strategies and feedback loops for LLM optimization.
- Capture and normalize LLM interactions into reusable Knowledge Artifacts.
- Integrate GenAI systems into enterprise apps (APIs, microservices, workflow engines)
- Programming languages: Python

2. Model Gateway & Multi-LLM Strategy

- Architect model gateways to access multiple LLMs (OpenAI, Anthropic, Cohere, etc.).
- Dynamically select models based on accuracy vs. cost trade-offs.
- Benchmark and evaluate models for enterprise-grade performance.

3. Agentic Workflows

- Design and implement agent-based orchestration for multi-step reasoning and autonomous task execution.
- Design and implement agentic workflows using industry-standard frameworks for autonomous task orchestration and multi-step reasoning.
- Ensure secure and controlled execution of agentic pipelines across enterprise systems via constraints, policies, and fallback paths.

4. Data Lakehouse & Knowledge Management

- Architect and maintain Lakehouse environments for structured and unstructured data.




- Implement pipelines for document parsing, chunking, and vectorization.
- Maintain knowledge stores, indexing, metadata governance
- Enable semantic search and retrieval using embeddings and vector databases.

5. Ontology & Taxonomy Engineering

- Build and maintain domain-specific ontologies and taxonomies.
- Establish taxonomy governance and versioning.
- Connect semantic registries with LLM learning cycles.
- Enable knowledge distillation from human/LLM feedback.

6. AI Governance & Knowledge Distillation

- Establish frameworks for semantic registry, prompt feedback, and knowledge harvesting.
- Ensure compliance, normalization, and promotion of LLM outputs as enterprise knowledge.

7. Observability & Cost Optimization

- Implement observability frameworks for GenAI systems (performance, latency, drift).
- Monitor and optimize token usage, inference cost, and model efficiency.
- Maintain dashboards for usage analytics & operational metrics.
- Make Build vs. Buy decisions based on cost-benefit analysis

📌 Staff Data Analytics Engineer (Bengaluru)
🏢 Sandisk
📍 Bengaluru