Senior Agentic AI Engineer

ITC Infotech; Gurugram District; On-site; INR 3,000,000 - 8,000,000; Full time

Job summary

ITC Infotech seeks a Senior Agentic AI Engineer to design, build, and operate production-grade Agentic AI, Decision Intelligence, and RAG solutions on Microsoft Azure for DSCS. You will support evolving business needs by delivering scalable, secure AI capabilities with explainability, governance, and observability across enterprise data and systems.

Responsibilities include designing single-agent and multi-agent architectures, integrating with MCP-based tools, and driving cost- and

Qualifications

• Bachelor's degree in Computer Science or a related field; Master’s preferred.
• 3+ years hands-on Generative AI/LLM app development, with Agentic AI experience.
• Strong Python, plus TypeScript/Node.js or similar for services.
• Proven production-grade cloud app design and deployment.
• Experience with Azure AI Foundry, Azure OpenAI, Azure AI Search, embeddings, vector search, grounding and citations.
• Experience with Agentic AI frameworks and MCP-based tool integration.

Responsibilities

• Design and build production-grade single-agent and multi-agent systems in Azure AI Foundry.
• Architect Generative AI solutions using Azure AI Foundry/OpenAI/Search and enterprise services.
• Develop RAG architectures with structured/unstructured data sources and grounding.
• Integrate agents with enterprise systems via MCP, REST APIs, and databases.
• Develop NL2SQL capabilities and secure data access.
• Define semantic-layer strategies for enterprise data models and metrics.
• Build Decision Intelligence capabilities to improve decision quality.
• Create reusable frameworks for impact analysis, prioritization, and traceability.
• Ensure explainability and governance of AI-generated recommendations.
• Establish observability, monitoring, and cost-optimized AI platforms.

Skills

Azure Foundry

Azure OpenAI

RAG

Agentic AI

MCP

NL2SQL

LLMOps

CI/CD

Python

REST APIs

Education

Bachelors in Computer Science or related field

Master's degree preferred

Tools

Azure AI Foundry

Azure OpenAI

Azure AI Search

Microsoft Agent Framework

Semantic Kernel

LangGraph

AutoGen

LLM APIs

Job description

Senior Agentic AI Engineer

We are seeking a hands-on Senior Agentic AI Engineer to design, build, and operate production-grade Agentic AI, Decision Intelligence, and Retrieval-Augmented Generation (RAG) solutions on Microsoft Azure for Bechtel s Digital Supply Chain Systems (DSCS) organization.

The role will support diverse and evolving DSCS business requirements by developing reusable, scalable, secure, and explainable enterprise AI capabilities.

Responsibilities

• Design and build production-grade single-agent and multi-agent systems in Azure AI Foundry capable of orchestrating reasoning, planning, tool usage, and workflow execution.
• Architect scalable Generative AI solutions leveraging Azure AI Foundry, Azure OpenAI, Azure AI Search, and other enterprise AI services.
• Build and govern RAG architectures using structured and unstructured enterprise data sources, including embeddings, vector/hybrid search, chunking, metadata filtering, reranking, grounding, and citations.
• Develop secure, reliable integrations between agents and enterprise systems using Model Context Protocol (MCP), REST APIs, relational databases, and event-driven services.
• Design Natural Language to SQL (NL2SQL) capabilities, ensuring accuracy, explainability, and secure access to enterprise data.
• Define semantic-layer strategies that enable AI agents to understand enterprise data models, business metrics, terminology, and relationships.
• Architect Decision Intelligence capabilities that combine enterprise data, business context, analytics, and AI reasoning to support informed decision-making.
• Establish reusable frameworks for impact analysis, dependency identification, prioritization, recommendation generation, and decision traceability.
• Ensure AI-generated recommendations are explainable, evidence-based, grounded in authoritative enterprise data, and aligned with business objectives.
• Define and automate evaluation methodologies for response quality, reasoning quality, recommendation relevance, business usefulness, and user trust, including golden datasets, LLM-based evaluation, and regression evaluations integrated into CI/CD.
• Implement Guardrails and Responsible AI controls, including input/output content safety, PII protection, grounding checks, authorization boundaries, and human-in-the-loop escalation paths.
• Establish governance, security, safety, transparency, and compliance standards for enterprise AI solutions.
• Implement observability and monitoring frameworks for AI applications, including quality, performance, reliability, and adoption metrics, along with traces, tool calls, latency, token usage, and cost.
• Optimize solutions for cost and latency through model selection, prompt and context engineering, caching, and workload right-sizing.
• Drive architectural decisions for scalable, cloud-native AI platforms using modern software engineering, DevOps, and MLOps/LLMOps practices.
• Define technical standards, reference architectures, and reusable frameworks for AI agents, reasoning systems, and decision-support applications.
• Mentor engineers and provide technical guidance on Agentic AI, Decision Intelligence, software architecture, and enterprise AI best practices.
• Partner with business stakeholders and domain experts to transform complex business requirements into reusable AI capabilities.
• Collaborate with data engineering teams to develop AI-ready data products, semantic models, metadata frameworks, and enterprise knowledge layers.
• Stay current with emerging AI technologies, frameworks, and industry practices, evaluating their applicability within DSCS and enterprise environments.

Education and Experience Requirements

• Bachelor's degree in Computer Science or a related field; Master's degree preferred, with 8+ years of relevant software engineering experience.
• 3+ years of hands-on experience developing Generative AI, machine learning, intelligent automation, or LLM-based applications, including substantial recent experience with Agentic AI.
• Strong programming proficiency in Python; working knowledge of TypeScript/Node.js or a comparable language for application services.
• Strong software engineering background with experience designing and deploying production-grade cloud applications.
• Hands-on experience building Generative AI and RAG applications with Azure AI Foundry, Azure OpenAI, Azure AI Search, LLM APIs, embeddings, vector or hybrid search, knowledge retrieval, grounding, and citations.
• Experience with Agentic AI frameworks such as Microsoft Agent Framework, Semantic Kernel, LangGraph, AutoGen, or comparable frameworks, including single-agent and multi-agent systems, tool calling, MCP-based tool integration, and human-in-the-loop controls.
• Experience building Natural Language to SQL (NL2SQL) or conversational analytics solutions, including schema and metadata modeling, query generation, query validation, and grounding answers in retrieved data.
• Experience designing or contributing to Decision Intelligence systems that combine AI, analytics, business context, and operational workflows to improve decision quality and business outcomes.
• Experience evaluating and improving agent quality through prompt engineering, test datasets, LLM-based evaluation, safety checks, reasoning-quality assessment, and production feedback loops.
• Strong knowledge of LLMOps, CI/CD, Docker, Kubernetes, observability, and production operations for AI applications.
• Working knowledge of core Azure platform services, including AKS or Azure Container Apps, Azure Functions, API Management, Entra ID, Key Vault, Azure SQL, or Cosmos DB.
• Good understanding of RESTful APIs, asynchronous patterns, secure integrations, relational databases, SQL, SQL/NoSQL data stores, and data engineering or ETL pipelines.
• Experience with enterprise-scale secure AI deployments, including identity, authorization, data privacy, compliance, and production monitoring.
• Strong analytical, problem-solving, collaboration, and communication skills.

Preferred / Nice-to-Have

• Experience with Microsoft Fabric, Azure Databricks, or Azure Data Factory for AI-ready data pipelines.
• Exposure to Copilot Studio, Power Platform, or Teams-based agent experiences.
• Experience with model fine-tuning, such as LoRA/QLoRA, prompt caching, and token/cost optimization at scale.
• Supply chain domain knowledge, including procurement, expediting, logistics, or materials management, or familiarity with ERP data such as Oracle EBS or SAP.
• Front-end experience with React and TypeScript for building agent-facing user interfaces.
• Microsoft certifications such as Azure AI Engineer Associate (AI-102/AI-103) or Azure Solutions Architect (AZ-305).

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