Software Engineer - Gen AI

BT Group; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

BT Group is seeking a seasoned AI-focused software engineer in Bengaluru to design, build, and deploy GenAI solutions across enterprise stacks. You will integrate copilots with Microsoft 365, Teams, and SharePoint while architecting robust RAG pipelines and secure API layers.

The role emphasizes collaboration with SAP teams, governance of AI components, and mentoring colleagues to scale AI capabilities responsibly.

Qualifications

• 5+ years of software engineering experience with AI in production.
• 2+ years with Generative AI, LLMs or applied ML.
• Hands-on with Azure OpenAI Service and AWS Bedrock.
• Experience integrating AI with SAP S/4HANA using APIs.

Responsibilities

• Design, develop, and deploy GenAI solutions using Azure OpenAI Service and AWS Bedrock.
• Publish enterprise copilots and integrate with M365, Teams, SharePoint, and Dataverse.
• Architect RAG pipelines with vector databases and knowledge bases.
• Develop prompt strategies to optimize output quality and consistency.
• Mentor junior engineers and work with product stakeholders.

Skills

Software engineering

Generative AI

LLMs

Python

TypeScript

REST APIs

CI/CD

Docker

Kubernetes

OpenSearch

SAP S/4HANA

Azure OpenAI

LangChain

LlamaIndex

Tools

Microsoft Copilot Studio

Azure AI Studio

LangChain

LlamaIndex

OData APIs

Job description

What you will be doing (Role Accountabilities)

• GenAI Platform Engineering:
• Design, develop, and deploy GenAI solutions using Azure OpenAI Service and AWS Bedrock, selecting appropriate foundation models (GPT-4o, Claude, Titan, Llama, Mistral) based on use-case requirements.
• Build, configure, and publish enterprise copilots using Microsoft Copilot Studio or equivalent low-code/pro-code frameworks, integrating with M365, Teams, SharePoint, and Dataverse.
• Architect and implement RAG (Retrieval-Augmented Generation) pipelines using vector databases (Azure AI Search, OpenSearch, Pinecone) and structured knowledge bases.
• Develop prompt engineering strategies including few-shot prompting, chain-of-thought, and system instruction design — to optimize LLM output quality and consistency.
• Enterprise System Integration:
• Integrate GenAI capabilities with SAP S/4HANA using OData APIs, SAP Business Accelerator Hub connectors, event-driven architectures (SAP Event Mesh, BTP), and workflow triggers
• Build and maintain secure API layers (REST, GraphQL) connecting AI services to ERP, CRM, and operational data sources
• Collaborate with SAP functional and Basis teams to align AI touchpoints with existing business processes, authorization models, and data governance policies
• Architecture & Collaboration:
• Contribute to GenAI architecture decisions including platform selection, cost optimization strategies, multi-region deployment, and security design.
• Mentor junior engineers and participate in internal knowledge sharing through design reviews, documentation, and community of practice sessions.
• Engage with product managers and business stakeholders to translate functional requirements into technically feasible AI solution designs.
• Evaluation, Monitoring & Responsible AI:
• Design and implement LLM evaluation frameworks covering accuracy, hallucination rates, latency, cost per token, and end-user satisfaction metrics.
• Establish monitoring pipelines for production AI applications using tools such as Azure Monitor, AWS CloudWatch, and LangSmith.
• Apply responsible AI practices including content filtering, guardrails (Azure Content Safety, Bedrock Guardrails), bias detection, and explainability mechanisms.
• Manage model versioning, deprecation cycles, and prompt version control to ensure production stability.

What you'll need to succeed (Skills & Experience)

• 5+ years of software engineering experience, with at least 2 years focused on Generative AI, LLMs, or applied ML in production environments.
• Hands‑on experience with Azure OpenAI Service and AWS Bedrock - including model deployment, API integration, token management, and cost governance.
• Practical experience building copilots or AI agents using Microsoft Copilot Studio, Azure AI Studio, LangChain, LlamaIndex, or equivalent agentic frameworks.
• Strong understanding of RAG architecture, vector embeddings, chunking strategies, and retrieval optimization.
• Proficiency in Python (primary) and at least one secondary language (TypeScript, Java, or Node.js).
• Experience integrating AI services with enterprise systems - ideally SAP S/4HANA - using OData, REST APIs, or event-driven patterns.
• Solid understanding of enterprise security requirements including OAuth 2.0, managed identities, RBAC, secret management, and data residency compliance.
• Familiarity with cloud platforms: Microsoft Azure (preferred), AWS, or GCP for deploying and scaling AI workloads.
• Experience with containerization (Docker, Kubernetes) and CI/CD pipelines for AI application deployments.
• Experience with SAP Joule and SAP AI Core.
• Knowledge of SAP BTP (Business Technology Platform) services, SAP Integration Suite, or SAP AI Core