GenAI & Agentic AI Lead / Architect (C2)

Capgemini; Navi Mumbai; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Capgemini Engineering seeks an experienced GenAI Architect to lead end-to-end AI strategy and deployment for enterprise-scale environments. You will architect solutions across J2EE, .NET, ERP, and related domains, evaluating options, and guiding ROI-driven decisions.

You will drive GenAI innovation through pilots, assets, and adoption of modern AI technologies, collaborating with delivery teams and stakeholders to align roadmaps with business goals.

Qualifications

• Ideal Profile: 9 to 12 years of IT experience with GenAI architecture, cloud AI platform expertise, Python-based AI/ML development, and enterprise-scale solution design experience.
• GenAI Agentic AI Expertise: Prompt Engineering, RAG, LangChain, Vector Databases, Text/Image Generation, AI Agent frameworks.
• Programming AI/ML: Python, Pandas, NumPy, Matplotlib, Scikit-learn, Data Preprocessing, Feature Engineering.
• Cloud AI Platforms: Azure OpenAI, AWS Bedrock, GCP AI Services, deployment of GenAI applications on cloud.
• Application Development Deployment: FastAPI, Flask, Streamlit, API integration and production deployment of AI solutions.
• Data Platform Skills: PostgreSQL, SQL/PL-SQL, Cloud Storage, Data Ingestion, Access Control, Key Vaults, and security best practices.

Responsibilities

• Architect and lead GenAI Agentic AI solutions for medium to large-scale enterprise environments across technologies such as J2EE, .NET, ERP, etc.
• Define end-to-end AI architecture, evaluate design alternatives, and perform cost-benefit and ROI analysis for technology decisions.
• Drive GenAI innovation through POCs, pilots, asset creation, and adoption of emerging AI technologies and platforms.
• Provide strategic technology roadmaps, architectural recommendations, and implementation guidance to delivery teams.
• Engage with stakeholders through strong communication, presentations, and cross-functional collaboration.

Skills

GenAI architecture

Cloud AI platform

Python-based AI/ML development

Enterprise-scale solution design

Tools

LangChain

Vector Databases

AI Agent frameworks

FastAPI

Flask

Streamlit

Job description

At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the worlds mostinnovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as theyprovide unique RD and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days arethe same.

Your Role

• Architect and lead GenAI Agentic AI solutions for medium to large-scale enterprise environments across technologies such as J2EE, .NET, ERP, etc.
• Define end-to-end AI architecture, evaluate design alternatives, and perform cost-benefit and ROI analysis for technology decisions.
• Drive GenAI innovation through POCs, pilots, asset creation, and adoption of emerging AI technologies and platforms.
• Provide strategic technology roadmaps, architectural recommendations, and implementation guidance to delivery teams.
• Engage with stakeholders through strong communication, presentations, and cross-functional collaboration.

Your Profile

• Ideal Profile: 9 to 12 years of IT experience with strong GenAI architecture, cloud AI platform expertise, Python-based AI/ML development, and enterprise-scale solution design experience.
• GenAI Agentic AI Expertise: Prompt Engineering, RAG, LangChain, Vector Databases, Text/Image Generation, AI Agent frameworks.
• Programming AI/ML: Python, Pandas, NumPy, Matplotlib, Scikit-learn, Data Preprocessing, Feature Engineering.
• Cloud AI Platforms: Azure OpenAI, AWS Bedrock, GCP AI Services, deployment of GenAI applications on cloud.
• Application Development Deployment: FastAPI, Flask, Streamlit, API integration and production deployment of AI solutions.
• Data Platform Skills: PostgreSQL, SQL/PL-SQL, Cloud Storage, Data Ingestion, Access Control, Key Vaults, and security best practices.