Artificial Intelligence Engineer

Job Title: AI Engineer (Generative AI / LLM Engineer)

Experience: 23 Years

Location: Bangalore (Hybrid preferred)

Budget: 10-14LPA

Role Overview:

We are looking for a hands-on AI Engineer with 23 years of experience to design, build, and

deploy Generative AI and machine learning powered applications. The ideal candidate should

be comfortable working with LLMs, embeddings, vector databases, and agent-based workflows

and should have experience integrating AI models into production systems and enterprise

workflows.

This role is application-engineering focused (not pure research). You will be building real AI

products such as chatbots, copilots, document intelligence systems, and knowledge assistants

using modern GenAI frameworks.

Key Responsibilities:

LLM & Generative AI Development

Build AI applications using LLMs (OpenAI, Gemini, Llama, Claude, or similar)

Implement RAG (Retrieval Augmented Generation) pipelines

Perform prompt engineering, prompt tuning, and evaluation of responses

Develop conversational AI assistants, copilots, and automation agents

Handle hallucination reduction, grounding, and response quality improvement

AI Application Engineering:

Use LangChain / LangGraph / CrewAI or similar agent frameworks

Integrate LLMs with APIs, databases, and enterprise applications

Build document processing systems (PDF, emails, knowledge bases)

Develop multi-step reasoning workflows and AI agents

Implement tool-using agents (search, database querying, workflows)

Data & Vector Infrastructure:

Create embeddings and semantic search pipelines

Work with vector databases such as:

o Pinecone / FAISS / ChromaDB / PostgreSQL (pgvector)

Implement chunking strategies, indexing, and retrieval optimization

Build scalable ingestion pipelines

Model Operations & Deployment:

Deploy models and applications via APIs and containers

Track and manage experiments using MLflow or similar

Monitor performance, latency, and response accuracy

Optimize token usage and inference cost

Implement evaluation metrics and feedback loops

Required Skills:

Programming & Core Tech

Python (must have)

Strong understanding of APIs, REST services, JSON

Git and version control

Basic SQL & database querying

AI/ML & GenAI:

Experience with LLM APIs (OpenAI / Azure OpenAI / Gemini / HuggingFace)

Prompt engineering and evaluation

Embeddings and semantic search

RAG architecture understanding

Familiarity with hallucination mitigation techniques

Frameworks & Tools:

LangChain or LangGraph

Vector databases (FAISS / Pinecone / ChromaDB / pgvector)

Transformers / HuggingFace (basic usage)

FastAPI / Flask for serving models

Docker (basic level)

Good to Have:

Knowledge of agent frameworks (CrewAI, AutoGen)

Web search grounding (Tavily or similar)

MCP (Model Context Protocol) usage

Basic cloud exposure (AWS / Azure / GCP)

Streamlit or Gradio UI apps

Fine-tuning or LoRA knowledge

Educational Qualification:

B.Tech / BE / MS in Computer Science, AI, Data Science, or related field

Relevant certifications or GenAI coursework preferred