AI Python Engineer- Bangalore- Immediate Joiner

Anlage Infotech; Bengaluru; On-site; INR 2,000,000 - 4,200,000; Full time

Job summary

Anlage Infotech in Bengaluru is seeking an experienced AI/GenAI Engineer to design, develop and deploy scalable AI-powered applications using LLMs, RAG, and Agentic AI frameworks.

The role emphasizes Python development, cloud-native deployments, and hands-on work with orchestration frameworks such as LangChain, LangGraph, CrewAI, AutoGen, and similar tools. You will build production-grade GenAI solutions and collaborate with product and engineering teams.

Qualifications

• Proficient in Python and AI/ML workflows.
• Experience with LLMs and production-grade deployments.
• Familiarity with cloud platforms (Azure/AWS/GCP).

Responsibilities

• Build and deploy GenAI apps using LLMs.
• Design RAG pipelines with embeddings and vector stores.
• Develop AI agents and orchestration workflows.
• Fine-tune, evaluate, and optimize LLMs for production.
• Integrate AI services into scalable backend APIs.
• Work with structured/unstructured datasets for NLP and AI workflows.
• Deploy AI solutions on cloud platforms such as Azure, AWS, or GCP.
• Build observability, monitoring, guardrails, and evaluation frameworks for GenAI systems.
• Collaborate with product, engineering, and business teams to deliver AI-driven solutions.
• Mentor junior engineers and contribute to AI architecture decisions (for senior roles).

Skills

Python

LLMs

RAG

LangChain

LangGraph

CrewAI

AutoGen

Cloud-native

NLP

APIs

Tools

LangChain

LangGraph

CrewAI

AutoGen

Vector databases

Embeddings

Job description

We are looking for an experienced AI/GenAI Engineer to design, develop, and deploy scalable AI-powered applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI frameworks/workflow development. The ideal candidate should have strong Python development skills, hands‑on experience with modern AI orchestration frameworks, and exposure to cloud-native AI deployments.

Key Responsibilities

• Build and deploy GenAI applications using LLMs such as GPT, Gemini, Llama, Mistral, Claude, etc.
• Design and implement RAG pipelines using vector databases and embeddings.
• Develop AI agents and workflow orchestration using LangChain, LangGraph, CrewAI, AutoGen, or similar frameworks.
• Fine-tune, evaluate, and optimize LLM models for production use cases.
• Integrate AI services into scalable backend systems and APIs.
• Work with structured/unstructured datasets for NLP and AI workflows.
• Deploy AI solutions on cloud platforms such as Azure, AWS, or GCP.
• Build observability, monitoring, guardrails, and evaluation frameworks for GenAI systems.
• Collaborate with product, engineering, and business teams to deliver AI-driven solutions.
• Mentor junior engineers and contribute to AI architecture decisions (for senior roles).