Artificial Intelligence Engineer

John Cockerill; Navi Mumbai; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

John Cockerill in Navi Mumbai (Ghansoli) is seeking an experienced AI Engineer to design and deliver AI-powered solutions across enterprise systems. You will build copilots, multi-agent architectures, and robust data pipelines, aligning with business requirements.

You will work with Microsoft Copilot Studio, Azure AI Foundry, Azure OpenAI, and related platforms to optimize performance, cost, and security while implementing governance and monitoring.

Qualifications

• Experience designing AI products for enterprise environments.
• Ability to translate user stories into AI solutions.
• Knowledge of cloud deployment and security for AI systems.

Responsibilities

• AI solution development and design across copilots and multi-agent systems.
• Build AI-powered assistants using Copilot Studio and Azure OpenAI.
• Develop reusable AI components and shared frameworks.
• Translate requirements into working AI solutions.
• Design interfaces, guardrails, and monitoring.
• Participate in architecture reviews and governance.
• Implement CI/CD, logging, and security for AI deployments.
• Establish LLMOps and MLOps pipelines.
• Ensure data integration with enterprise systems.
• Monitor costs, latency, and model performance.

Skills

LLM prompts

MLOps

Multi-agent systems

Python

Tools

Microsoft Copilot Studio

Azure OpenAI

Azure AI Foundry

Microsoft Graph

Power Platform

Azure Services

Job description

We are having an excellent job opportunity for AI Engineer role at Ghansoli Navi Mumbai location.

Key Responsibilities

• AI Solution Development Design and develop AI applications, copilots, and multi-agent systems aligned with approved business requirements.
• Build AI-powered assistants using Microsoft Copilot Studio, Azure AI Foundry, Azure OpenAI, Microsoft Graph, Power Platform and Azure Services.
• Develop reusable AI components and shared frameworks.
• Translate user stories and functional requirements into working AI solutions.
• Agentic AI Engineering Design and develop multi-agent systems using approved architecture.
• Implement orchestration frameworks, agent collaboration patterns, tool calling, memory management, and human-in-the-loop controls.
• Design agent interfaces, workflows, guardrails, and monitoring capabilities.
• Participate in architecture reviews and technical governance.
• Prompt Engineering & Model Development Create, test, optimize, and document prompts.
• Evaluate AI model performance.
• Develop Retrieval Augmented Generation (RAG) solutions.
• Implement vector search and semantic retrieval capabilities.
• Optimize accuracy, latency, and cost.
• Data & Integration Engineering Integrate AI products with enterprise systems including SAP S/4HANA, JD Edwards, Planview, SharePoint, Teams, Microsoft 365 and engineering platforms.
• Design APIs and data pipelines.
• Ensure secure handling of enterprise data.
• Cloud & Platform Engineering Deploy solutions on approved cloud environments.
• Implement CI/CD pipelines.
• Configure monitoring, logging, and alerting.
• Support infrastructure automation and environment management.
• LLMOps / MLOps Establish deployment pipelines for AI products.
• Manage AI lifecycle activities: development, testing, validation, deployment, monitoring and retirement.
• Monitor token consumption and cloud costs.
• Implement model governance and version control.
• Security, Risk & Compliance Ensure compliance with Group AI Policy, Energy AI Governance SOP, cybersecurity standards, data privacy requirements and EU AI Act requirements.
• Participate in risk assessments and architecture reviews.
• Support audit and compliance activities.
• Quality Assurance Conduct model testing and validation.
• Measure accuracy and business performance.
• Execute AI evaluation frameworks.
• Document known limitations and mitigation actions.
• Documentation & Knowledge Management Maintain technical documentation.
• Create architecture diagrams and deployment guides.
• Produce support documentation and training materials.
• Ensure solutions can be maintained independently of individual developers.
• Adoption & Continuous Improvement Support pilots, Proofs of Concept (PoCs), and production rollouts.
• Troubleshoot production issues.
• Analyze usage patterns and user feedback.
• Recommend enhancements that improve business outcomes.