AI/ML Computational Science Analyst

Designation: AI/ML Computational Science Analyst

About Accenture
Accenture is a global professional services company with leading capabilities in digital, cloud and security.Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Technology and Operations services, and Accenture Song— all powered by the world's largest network of Advanced Technology and Intelligent Operations centers. Our 784,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries.

What would you do
Reinvention Deployment Engineering (RDE) is an approach used by Accenture to reimagine and accelerate the delivery of engineering and R&D solutions. It focuses on combining human expertise with AI-driven agents to enhance innovation velocity, streamline processes, and reduce time to market products and services.

Must Have Skills

• Python & Full-Stack Development
• Agentic AI (LangChain, LangGraph, MCP, RAG)
• Good Python programming fundamentals including scripting, data structures and Object-Oriented Programming concepts.
• Basic exposure to AI/ML concepts, GenAI, prompt engineering or LLM-enabled applications.
• Understanding of REST APIs, JSON, Git and software development lifecycle basics.

Skill Area

• Agentic AI Concepts - Deep understanding of AI agent design, reasoning loops, orchestration patterns & multi-agent coordination architectures. Core differentiator; senior levels lead architecture design
• LLM & Prompt Engineering - Hands-on with LLMs (GPT-4, Claude, Gemini); prompt engineering, few-shot, chain-of-thought & structured output techniques.
• AI Frameworks - Exposure in LangGraph, LangChain for production-grade agentic workflow development.
• Programming & APIs - Strong Python skills — async programming, OOP, data structures & scripting for AI pipelines; Java/.NET acceptable. Python strongly preferred for AI workloads
• Cloud & DevOps - Azure / AWS / GCP hands-on experience; cloud-native architecture. CI/CD mandatory.

Roles and Responsibilities:

• Support development of Python-led AI/ML components, scripts and AI pipeline utilities under guidance from senior engineers.
• Assist in prompt engineering, structured output testing, basic RAG implementation, and validation of LLM responses.
• Participate in API testing, integration validation, documentation, and defect resolution activities.