Sr. Data Scientist, AI Engineering
Trinity Life Sciences
- Location
- Bangalore Urban, Karnataka, India
- Job type
- Full-time
Required skills
- LangChain
- Python
- AWS
- Azure
- GCP
- microservices
- NLP
- PostgreSQL
About the role
Trinity Life Sciences
Website:
trinitylifesciences.com
Job details:
We're committed to bringing passion and customer focus to the business.
Key Responsibilities
- Architect and implement RAG pipelines, agentic AI systems, and LLM-driven applications for enterprise use cases.
- Design and integrate prompt engineering, context management, and knowledge-grounding frameworks to optimize LLM performance.
- Collaborate with data, ML, and software engineering teams to build production-grade GenAI microservices and APIs.
- Evaluate and integrate open-source and proprietary LLMs (e.g., OpenAI, Anthropic, Mistral, Llama, Gemini).
- Design data pipelines for unstructured/structured content ingestion, indexing, and vector retrieval using Milvus, PostgreSQL (pgvector), or similar technologies.
- Define and enforce architecture standards, governance, and best practices for scalable GenAI platforms.
- Conduct PoCs, benchmark model performance, and lead solution transitions from prototype to production.
- Contribute to AI strategy, model lifecycle management, and cost optimization initiatives.
Required Skills And Qualifications
- Bachelor’s/Master’s degree in Computer Science, AI, Data Engineering, or related field.
- 5–8 years of total experience, with at least 3+ years in AI/ML or NLP systems design.
- Proven experience implementing LLM-based solutions, RAG architectures, and prompt orchestration frameworks.
- Strong Python programming skills and familiarity with frameworks like LangChain, LangGraph, LlamaIndex, or Transformers.
- Hands-on knowledge of vector databases (Milvus, Pinecone, Weaviate, Chroma) and knowledge graph systems (Neo4j, RDF).
- Experience deploying and managing AI workloads on cloud platforms (GCP, Azure, AWS).
- Understanding of MLOps/GenAIOps, model evaluation, and observability practices.
- Strong problem-solving, communication, and stakeholder management capabilities.
Preferred Skills
- Experience with multimodal LLMs, agentic reasoning, and tool-using AI agents.
- Exposure to pharma/life sciences or regulated enterprise domains.
- Contribution to open-source AI frameworks or internal AI accelerators.
Click on Apply to know more.
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