Gen AI Engineer

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

Job summary

Evnek in Bengaluru is seeking an experienced Generative AI Engineer with a strong data background and hands-on expertise in modern AI technologies. The candidate should have delivered multiple GenAI solutions and be proficient in RAG, Agentic AI, and integrating LLMs with enterprise data.

The role requires ownership of end-to-end GenAI projects, collaboration with data teams, and delivering scalable backend services. Knowledge of LangChain, vector databases, and cloud AI platforms is preferred.

Qualifications

• Must have delivered 3–5 GenAI projects or products.
• Hands-on experience with RAG-based applications.
• Hands-on experience with Agentic AI or AI Agent workflows.
• Strong data background in Data Engineering, Data Science, Data Analytics, or Python Development.

Responsibilities

• Design, develop, and deploy scalable GenAI solutions for business use cases.
• Build and optimize RAG pipelines using LLMs and data sources.
• Develop Agentic AI solutions with autonomous reasoning, planning, and tool use.
• Design AI agents and multi-agent workflows for complex processes.
• Integrate LLMs with structured and unstructured enterprise data.
• Collaborate with Data Engineering/Science and business teams to identify use cases.
• Develop APIs and backend services to support GenAI apps.
• Evaluate and optimize LLM performance for accuracy and latency.
• Implement vector search, embeddings, and semantic retrieval.

Skills

Generative AI

Python

LLMs

RAG

Agentic AI

Data Engineering

Data Science

Data Analytics

Tools

LangChain

LangGraph

LlamaIndex

Pinecone

FAISS

Chroma

Weaviate

Milvus

Job description

Notice Period: Immediate Joiners Preferred

Job Overview

We are looking for an experienced Generative AI Engineer with a strong background in data and hands-on expertise in modern AI technologies. The ideal candidate should have previously worked as a Data Analyst, Data Engineer, Data Scientist, or Python Developer and should have successfully designed and delivered multiple Generative AI solutions.

The candidate must have practical experience in Generative AI, Retrieval-Augmented Generation (RAG), and Agentic AI, with a proven track record of delivering at least 3–5 GenAI-based projects or products.

Key Responsibilities

• Design, develop, and deploy scalable Generative AI solutions for business and enterprise use cases.
• Build and optimize RAG (Retrieval-Augmented Generation) pipelines using LLMs and enterprise data sources.
• Develop Agentic AI solutions capable of autonomous reasoning, planning, decision-making, and tool usage.
• Design and implement AI agents and multi-agent workflows for complex business processes.
• Integrate Large Language Models (LLMs) with structured and unstructured enterprise data.
• Work closely with Data Engineering, Data Science, and business teams to identify and develop AI use cases.
• Develop APIs and backend services to support GenAI applications and products.
• Evaluate, fine-tune, and optimize LLM performance for accuracy, relevance, latency, and scalability.
• Implement vector search, embeddings, and semantic retrieval solutions.
• Ensure GenAI applications follow best practices related to security, governance, scalability, and responsible AI.
• Take ownership of the end-to-end delivery of GenAI projects from solution design through production deployment.

Required Skills

• 6–15 years of overall IT experience.
• Strong previous experience in one or more of the following roles:
• Data Engineer or Data Scientist or Data Analyst

Python Developer

• Strong hands-on programming experience in Python.
• Hands-on experience with Generative AI and Large Language Models (LLMs).
• Strong practical experience in:
• Retrieval-Augmented Generation (RAG)

Agentic AI

• AI Agents and Multi-Agent Systems
• Prompt Engineering
• Embeddings and Semantic Search
• Vector Databases
• Experience with GenAI frameworks such as LangChain, LangGraph, LlamaIndex, or similar frameworks.
• Experience working with LLMs such as OpenAI GPT models, Claude, Llama, Gemini, or other open-source/commercial models.
• Experience with vector databases such as Pinecone, FAISS, Chroma, Weaviate, Milvus, or similar.
• Strong understanding of data processing, data pipelines, APIs, and databases.
• Experience deploying AI/ML or GenAI applications into production environments.
• Knowledge of cloud AI platforms such as AWS Bedrock, Azure OpenAI, Google Vertex AI, or similar is preferred.

Mandatory Experience

• Must have successfully delivered at least 3–5 Generative AI-based projects or products.
• Demonstrated hands-on experience in building and deploying RAG-based applications.
• Demonstrated hands-on experience with Agentic AI or AI Agent workflows.
• Strong data background with previous experience in Data Engineering, Data Science, Data Analytics, or Python Development.