AI Engineer

BT Group; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

BT Group in Bengaluru is seeking an experienced AI platform engineer to build and own AI service features within Mind.AI. You will translate feature specifications into production-quality implementations, write tests, benchmark, and ship to the Lead AI Engineer.

The role covers RAG and knowledge retrieval, safety and guardrails, memory management, multi-agent AI, and robust data platforms. You will work with Kafka, NATS, REST APIs, and modern ML stacks to deliver scalable, low-latency services.

Qualifications

• Experience with distributed systems and microservices architecture.
• Knowledge of event-driven systems using Kafka and NATS.
• Skilled in REST APIs, real-time communication, API security, JWT, rate limiting, and resilience patterns.
• Experience building AI agents using LangChain and LangGraph.
• Strong understanding of prompt engineering, context management, memory, and multi-LLM integration.

Responsibilities

• Build and optimise enterprise-grade RAG pipelines for accurate knowledge retrieval.
• Develop document ingestion, indexing, embedding, and retrieval workflows.
• Design and implement long-term AI memory frameworks and knowledge retention capabilities.
• Define and implement AI evaluation metrics and testing frameworks; create golden datasets.
• Design scalable, production-ready AI services and APIs; optimise latency, throughput, and cost.
• Develop autonomous AI agents and multi-agent workflows; build orchestration frameworks for planning and task execution.

Skills

Distributed systems

Microservices architecture

Event-driven systems

REST APIs

API security

JWT

Rate limiting

Resilience patterns

Prompt engineering

LangChain / LangGraph

Tools

Kafka

NATS

PostgreSQL

pgvector

Redis

Elasticsearch / BM25

Neo4j

vLLM

ONNX

LoRA/QLoRA

Job description

You will build and own scoped AI service features within the Mind.AI platform. You work within the architecture set by the Lead AI Engineer, take feature specifications and deliver production-quality implementations: a chunking strategy module, a guardrail model integration, an embedding pipeline stage, a RAGAS metric computation job. You are expected to work independently within scope - take ownership, write tests, benchmark your work, and ship to the Lead's quality bar.

What you will be doing (Role Accountabilities)

1.RAG & Knowledge Retrieval

• Build and optimise enterprise-grade RAG pipelines for accurate knowledge retrieval
• Develop document ingestion, indexing, embedding, and retrieval workflows.

2. AI Safety & Guardrails

• Implement PII detection, data protection, and content redaction controls
• Integrate prompt injection, toxicity, and misuse detection mechanisms

3.Memory & Knowledge Management

• Design and implement long-term AI memory frameworks
• Build user, agent, and organisational knowledge retention capabilities
• Define and implement AI evaluation metrics and testing frameworks
• Create and maintain golden datasets for model validation
• Design scalable, production-ready AI services and APIs
• Optimise latency, throughput, reliability, and cost of AI workloads

6.Agentic AI & Multi-Agent Systems

• Design and develop autonomous AI agents and multi-agent workflows
• Build orchestration frameworks for planning, reasoning, and task execution

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

• Experience with distributed systems and microservices architecture.
• Knowledge of event-driven systems using Kafka and NATS.
• Skilled in REST APIs, real-time communication, API security, JWT, rate limiting, and resilience patterns.

2. LLM Orchestration & Agentic AI

• Experience building AI agents using LangChain and LangGraph.
• Skilled in single-agent and multi-agent workflows, including ReAct, Planning, and Tool-Use patterns.
• Strong understanding of prompt engineering, context management, memory, and multi-LLM integration.

3. Python & AI/ML Stack

• Strong programming skills in Python, FastAPI, and Pydantic.
• Experience with NLP and AI frameworks including SpaCy, Sentence Transformers, PyTorch, and Hugging Face.
• Knowledge of ONNX, LoRA/QLoRA fine-tuning, vLLM, LangChain, LangGraph, and RAGAS.

4. Retrieval & Search

• Skilled in document chunking, embeddings, vector databases, and Elasticsearch (BM25).
• Knowledge of hybrid search and cross-encoder re-ranking techniques.

5. Evaluation, Safety & Responsible AI

• Experience with AI evaluation frameworks such as RAGAS and DeepEval.
• Skilled in benchmarking, LLM-as-a-Judge, and human-in-the-loop evaluation.
• Knowledge of AI safety, prompt injection prevention, red teaming, and industry safety benchmarks.

6. Data Platforms

• Experience with PostgreSQL, pgvector, and Redis.
• Knowledge of Kafka for event streaming and data processing.
• Skilled in building and working with Neo4j knowledge graphs.

BT is the UK’s leading communications group and the holding company behind some of the country’s most recognised brands - including BT, EE, Openreach and Plusnet. Our purpose is as simple as it is ambitious: we connect for good. Our customers include consumers, small, medium and large businesses, public sector organisations and other communications providers.

Having come through the most capital-intensive phase of our fibre investment, our focus now is on what comes next - simplifying how we operate, using technology and AI to work smarter, and organising ourselves to serve customers better and grow sustainably.

We have a singular culture that unites all our people: we are customer-first challengers, who are committed, clear and connected. These behaviours unite us as one team to deliver for our colleagues, our customers, our stakeholders and the country. Joining BT means working at the heart of a business that matters to the UK, with the opportunity to shape decisions, influence outcomes and help set the future course of one of the country’s most important companies.