AI Engineer

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

Job summary

TECEZE is seeking an experienced AI Engineer in Bengaluru to build scalable GenAI solutions spanning RAG architectures, MCP endpoints and end-to-end AI orchestration. The role focuses on production-ready AI systems, leveraging Python, LLMs and vector databases in a fast-paced environment.

You will collaborate on data ingestion pipelines, model integration and multi-agent workflows, with emphasis on performance monitoring and reliability in production deployments.

Qualifications

• 6–8+ years of Python development experience.

Responsibilities

• Design end-to-end RAG architectures, ingestion pipelines and chunking strategies.

Skills

Python

GenAI

LLMs

RAG

MCP

Agentic AI

A2A

Multi-Agent workflows

APIs

Pipelines

AI orchestration

GitHub Copilot

Vector databases

Vector search

Datadog

Azure AI Foundry

Microsoft Fabric

Java

ReactJS

Tools

GitHub Copilot

Datadog

Azure AI Foundry

Microsoft Fabric

Job description

We are looking for an experienced AI Engineer with strong hands‑on experience in Python, GenAI, LLMs, RAG, MCP, and Agentic AI.

• 6–8+ years of strong Python development experience
• 3+ years of hands‑on AI/GenAI project experience
• Experience productizing AI solutions
• Hands‑on experience with commercial LLMs
• Strong knowledge of prompting patterns and structured outputs
• End‑to‑end RAG architecture, ingestion pipelines and chunking strategies
• Experience with Vector Databases / Vector Search, indexing, similarity search and metadata filtering
• Hands‑on experience with MCP (Model Context Protocol)
• Experience designing MCP servers/tool endpoints and integrating them with LLM applications
• Experience with Agentic AI / A2A / Multi‑Agent workflows such as planner, executor, reviewer and retriever patterns
• Advanced Python
• Experience building APIs, pipelines and AI orchestration
• Java / ReactJS is a plus

Development Productivity

• Hands‑on experience using GitHub Copilot for code acceleration, scaffolding services, APIs and development

Data

• Query writing, joins and indexing awareness
• Microsoft Fabric is a plus
• Microsoft Azure AI Foundry experience preferred
• Experience supporting AI-enabled services in production
• Logging, metrics and distributed tracing
• APM/observability tools such as Datadog
• Model/prompt monitoring, drift signals and quality regression detection