GenAI Engineer / AI Agent Engineer – AI Foundry & Copilot Studio

DXC Technology; Mumbai; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

DXC Technology in Mumbai seeks a software engineer specializing in AI agents and GenAI to design, build, and deploy production-ready agent workflows using Foundry and Copilot Studio.

You will implement core capabilities such as tool calling, memory patterns, RAG pipelines, and governance, ensuring security, testing, and observability across deployments while collaborating with cross-functional teams to deliver measurable outcomes.

Qualifications

• 3-5 years in software engineering with production deployment experience.

Responsibilities

• Design, build, and deploy AI agents using Foundry + Studio.

Skills

Python

Java

TypeScript

LLM prompts

Agent workflows

RAG

CI/CD

Testing

Tools

AI Foundry

Copilot Studio

LangChain

Semantic Kernel

Azure OpenAI

OpenAI

Job description

Job Description:

Key Responsibilities

AI Agents & GenAI Solution Development

• Design, build, and deploy AI agents using Foundry + Studio to solve real business problems
• Implement core agent capabilities:
  • Tool/function calling, multi-step planning, task decomposition
  • Retrieval-Augmented Generation (RAG) with enterprise knowledge sources
  • Memory patterns (session/state, long-term memory with governance)
  • Guardrails (policy checks, prompt safety, structured outputs)
• Develop agent workflows integrating:
  • APIs, databases, event-driven services, internal tools
  • Approval loops, HITL (Human-in-the-Loop), and escalation handling

Data & Knowledge Integration

• Build and optimize RAG pipelines:
  • Document ingestion, chunking, embedding strategies
  • Vector search
  • Grounding, citations, and source traceability
• Connect enterprise data sources in AI Foundry (datasets, ontology/semantic models where applicable) and operationalize for agent usage.

Engineering Excellence (Production Readiness)

• Create evaluation frameworks for GenAI:
  • Automated tests for factuality/grounding, relevance, toxicity, refusal correctness
  • Offline + online evaluation, regression testing for prompts and agent tools
• Implement observability:
  • Agent traces, tool-call logs, latency/cost metrics, failure modes
• Ensure security, compliance, and governance:
  • Access control, secrets management, PII handling
  • Model usage policies, auditability, and change management

Collaboration & Delivery

• Partner with stakeholders to translate requirements into agent designs and deliver measurable outcomes.
• Contribute to reusable libraries, templates, and best practices for Foundry/Studio agent development.

Required Qualifications (Must-Have)

• 3-5 years in software engineering (Python/Java/TypeScript or similar) with production deployment experience.
• Hands-on experience building AI agents in AI Foundry and Copilot Studio (agent workflows, tool integration, deployment).
• Strong understanding of LLMs and prompting patterns:
  • System prompts, structured outputs (JSON), function/tool calling, chain-of-thought-safe patterns
• Solid experience with RAG and search:
  • Embeddings, vector databases/search, chunking, reranking, grounding techniques
• Experience integrating GenAI solutions with:
  • REST APIs, microservices, message queues, databases
• Familiarity with software engineering best practices:
  • Unit/integration testing, CI/CD, code reviews, documentation

Preferred Qualifications (Nice-to-Have)

• Experience with one or more agent frameworks/concepts:
  • LangGraph/LangChain, Semantic Kernel, AutoGen-style orchestration patterns
• Experience with model providers and deployment patterns:
  • Azure OpenAI / OpenAI / open-source models
• Exposure to governance and compliance in enterprise AI:
  • Data classification, audit logging, model risk management

Core Technical Skills (Current GenAI Stack)

• Languages: Python (preferred), Java/TypeScript (plus)
• GenAI/LLM: Prompt engineering, tool calling, structured outputs, safety patterns
• AI Foundry & Copilot Studio: Building pipelines, deploying apps/workflows/agents, access controls
• Agents: Planning + tools + memory + orchestration; multi-agent (optional)
• RAG: Embeddings, retrieval strategies, reranking, grounding/citations
• Evaluation: Golden datasets, automated evals, human review loops, regression testing
• MLOps/DevOps: CI/CD, containerization, monitoring, performance/cost optimization

At DXC Technology, we believe strong connections and community are key to our success. Our work model prioritizes in-person collaboration while offering flexibility to support wellbeing, productivity, individual work styles, and life circumstances. We're committed to fostering an inclusive environment where everyone can thrive.