Sr. Data Scientist, AI Engineering

Trinity Life Sciences; Gurugram District; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Trinity Life Sciences in Gurugram, India seeks an experienced AI Architect to design and implement enterprise GenAI platforms. You will architect RAG pipelines, agentic AI systems, and LLM-driven applications, defining data ingestions, vector stores, and governance standards.

Collaborate with data, ML, and software teams to deploy production-grade microservices and ensure cost-efficient operations, model lifecycle management, and observability across cloud environments (GCP/AWS/Azure).

Qualifications

• Bachelor’s/Master’s degree in Computer Science, AI, Data Engineering, or related field.
• 5-8 years 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.

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.

Skills

GenAI architecture

RAG pipelines

Prompt orchestration

Python

LangChain

LangGraph

LlamaIndex

Transformers

Vector databases

Milvus

Pinecone

Weaviate

Chroma

Knowledge graphs

Neo4j

RDF

Cloud platforms

GCP

Azure

AWS

MLOps

GenAIOps

Observability

Communication

Stakeholder management

Education

Bachelor’s/Master’s in CS/AI/Data Eng

Tools

Milvus

Pinecone

Weaviate

Chroma

Neo4j

RDF

GCP

Azure

AWS

LangChain

LangGraph

LlamaIndex

Transformers

Job description

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.