AI/ML Computational Science Associate Manager

Accenture; Bengaluru; On-site; INR 2,500,000 - 4,500,000; Full time

Job summary

Accenture seeks an experienced AI/ML professional to lead the design, development and deployment of agentic AI solutions within its RDE PODs. The role combines hands-on Python engineering with AI strategy, integration, and cloud readiness across enterprise platforms.

You will work on state-of-the-art AI initiatives, including LangChain, LangGraph and RAG-enabled pipelines, ensuring responsible AI and scalable, observable production systems for clients globally.

Qualifications

• Strong Python engineering experience including async programming and OOP.
• Experience with GenAI LLM solution development and prompt engineering.
• Knowledge of RAG pipelines, vector databases and semantic search.

Responsibilities

• Lead design and development of Python-led agentic AI solutions and orchestrations.
• Define LLM-enabled solution patterns using prompts, RAG, vector databases and enterprise grounding approaches.
• Evaluate agentic AI frameworks and plan across APIs, microservices and enterprise platforms.
• Drive cloud/DevOps readiness with Docker, Kubernetes, CI/CD and security guardrails.

Skills

Python

Agentic AI

LangChain

RAG pipelines

Vector databases

Semantic search

Education

BE/BTech

Tools

LangGraph

Semantic Kernel

CrewAI

Job description

Skill required: Tech for Operations - Artificial Intelligence (AI)

Designation: RDE AIML Computational Science Assoc Mgr

Qualifications: BE/BTech

Years of Experience: 8 to 12 years

Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Technology and Operations services, and Accenture Songall powered by the worlds 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 Deployed Engineer (RDE) is an approach used by Accenture to reimagine and accelerate the delivery of engineering and RD solutions. It focuses on combining human expertise with AI-driven agents to enhance innovation velocity, streamline processes, and reduce time to market for products and services. RDE emphasizes a value-driven mindset, where humans define objectives and ethical guardrails while AI agenthandle scale, speed, and data-driven execution. The RDE AIML Computational Science Assoc Manager Agentic AI Integration will design, build, integrate, test and deploy AI native and Agentic AI solutions for Accenture Operations RDE PODs. The role is intended for multi skilled engineers with Python and AIML as the primary capability, supported by working knowledge across integration, cloud, DevOps, testingobservability, responsible AI and enterprise platforms The role supports the RDE POD model where engineers are expected to operate close to client problems, contribute across the delivery lifecycle, reduce handoffs, and accelerate client-facing outcomes through compact, T shaped teams. The hiring approach should therefore prioritize strong primary skill depth plus adjacent skill breadth

What are we looking for

Python, Full Stack Development, Agentic AI LangChain, LangGraph, MCP, RAG,. Strong Python engineering experience including async programming, Object Oriented Programming, data structures, scripting and production grade AI pipeline development. Hand on experience with GenAI LLM solution development, prompt engineering, structured outputs, RAG pipelines, vector databases and semantic search.Practical understanding of Agentic AI design patterns including orchestration, tool use, function calling, state management, memory and multi-agent coordination.

Roles and Responsibilities

Lead design and development of Python led Agentic AI solutions, including agent workflows, orchestration, tool calling, function routing, memory state management and multi agent coordination. Define and implement LLM enabled solution patterns using prompt engineering, structured outputs, RAG, vector databases, semantic search and enterprise grounding approaches. Evaluate and recommend agentic AI frameworks such as LangGraph, LangChain, Semantic Kernel and CrewAI based on use case complexity, maintainability, scalability and enterprise readiness. Own integration design across APIs, microservices and enterprise platforms such as ServiceNow, Appian, SAP, Salesforce, Microsoft 365, Teams and Power Platform.Drive cloud and DevOps readiness using Azure, AWS or GCP, including Docker, Kubernetes, CI CD, GitOps, infrastructure automation and deployment governance.Establish testing, observability and LLM evaluation practices covering AI output quality, tracing, monitoring, performance, cost optimization and production support readiness. Embed responsible AI, security, identity, compliance and guardrail requirements into solution design, including OAuth, Azure AD, data protection and enterprise risk controls. Coach junior engineers, review designs and code, unblock technical delivery, and enable RDE POD members to operate as T shaped, multi skilled contributors.

Qualification

BE,BTech