AI/ML Computational Science Specialist

AI/ML Computational Science Specialist

Experience: 5–8 Years

Designation: AI/ML Computational Science Specialist

Skill Required: Artificial Intelligence (AI)

Qualification: BTech / BE / BCA

Language: English (International) – Intermediate

Role Overview

The RDE-AI/ML Computational Science Specialist will design, build, integrate, test, and deploy AI-native and Agentic AI solutions.

The role requires strong Python and AI/ML capability, supported by working knowledge across integration, cloud, DevOps, testing, observability, responsible AI, and enterprise platforms.

Key Responsibilities

Own design and build of complex Python-led AI/ML and Agentic AI modules across the delivery lifecycle.

Design and implement agent workflows, tool-calling patterns, RAG pipelines, vector search, and enterprise grounding approaches.

Guide junior engineers through code reviews, design clarifications, testing practices, and technical issue resolution.

Drive API, microservices, and enterprise platform integration readiness.

Contribute to AI testing, observability, responsible AI controls, monitoring, performance optimization, and production support.

Must-Have Skills

Python & Full-Stack Development

Strong Python engineering

Async programming

OOP

Data structures

Scripting

Production AI pipeline development

Agentic AI

LangChain

LangGraph

MCP

RAG

Agent orchestration

Tool use

Function calling

Memory/state management

Workflow design

GenAI / LLM

GenAI and LLMs

Prompt engineering

Structured outputs

RAG

Vector databases

Semantic search

Integration & Engineering

REST APIs

Microservices

Enterprise integration

Testing

Debugging

Secondary Skills

LangGraph, LangChain, Semantic Kernel, CrewAI or equivalent

Azure / AWS / GCP

Docker

Kubernetes

CI/CD

GitOps

Deployment automation

Responsible AI

LLMOps

AI evaluation

Monitoring

OAuth

Azure AD

Enterprise security practices

Additional Technical Areas

AI agent design and reasoning loops

Orchestration and multi-agent coordination

Tool calling and function routing

Agent memory and state management

LLMs such as GPT, Claude, Gemini

Few-shot and structured output techniques

Vector databases such as Pinecone, Weaviate, and ChromaDB

REST/GraphQL API development

Cloud-native architecture

Managed AI services

Docker/Kubernetes

CI/CD and automated deployment

AI guardrails and enterprise compliance

LLM output evaluation

Observability and tracing

Performance tuning and cost optimization

Enterprise integration with platforms such as ServiceNow, Appian, SAP, Salesforce, and Microsoft ecosystem

Pay: Up to ₹1,800,000.00 per year

Work Location: In person