Generative AI Engineer

Evnek Technologies Pvt Ltd; Bengaluru; On-site; INR 1,500,000 - 2,000,000; Full time

Job summary

Evnek Technologies Pvt Ltd in Bengaluru seeks a highly skilled Generative AI Engineer to design, build and deploy production-grade GenAI solutions. You will optimize RAG pipelines, develop LLM workflows, and create AI agents integrated with enterprise data sources.

The role involves working with OpenAI/Azure OpenAI, Claude, Gemini, and other models, focusing on prompt engineering, embeddings, vector databases, and scalable APIs hosted on cloud platforms.

Qualifications

• Extensive hands-on GenAI experience in production.
• Strong Python programming skills.
• Experience with LLMs, RAG, and AI Agents.
• Experience with vector databases and embeddings.
• Experience deploying GenAI on cloud platforms.
• Experience taking GenAI from POC to production.

Responsibilities

• Design, build, and deploy end-to-end Generative AI solutions for enterprise use cases.
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines.
• Develop LLM workflows, AI Agents, and Agentic AI solutions.
• Work with LLMs such as OpenAI/Azure OpenAI, Claude, Gemini, Llama, or equivalent models.
• Design effective prompt engineering strategies and optimize LLM responses.
• Implement document ingestion, chunking, embeddings, retrieval, reranking, and response-generation pipelines.
• Develop APIs and AI services using Python and FastAPI/Flask.
• Work with Vector Databases such as Pinecone, FAISS, Chroma, Weaviate, or Azure AI Search.
• Integrate GenAI solutions with enterprise data sources, applications, databases, and APIs.
• Implement LLM evaluation, guardrails, monitoring, security, and responsible AI practices.
• Deploy and manage GenAI applications on Azure, AWS, or GCP.
• Optimize AI solutions for accuracy, scalability, latency, reliability, and cost.
• Collaborate with business stakeholders, architects, data engineers, and AI teams to deliver production-ready solutions.

Skills

Python

LLMs

RAG

Agentic AI

AI Agents

Prompt Engineering

Vector Databases

LangChain

LangGraph

LlamaIndex

Semantic Kernel

Embeddings

Vector Search

REST APIs

Docker

Git

CI/CD

Azure OpenAI

AWS Bedrock

Google Vertex AI

Production Deployment

Tools

FastAPI

Flask

Docker

Git

CI/CD pipelines

Job description

We are looking for a highly skilled Generative AI Engineer with hands-on experience in building and deploying production-grade GenAI solutions. The ideal candidate should have strong expertise in LLMs, RAG, Agentic AI, AI Agents, Python, prompt engineering, and vector databases.

Key Responsibilities

• Design, develop, and deploy end-to-end Generative AI solutions for enterprise use cases.
  
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines.
  
• Develop LLM workflows, AI Agents, and Agentic AI solutions.
  
• Work with LLMs such as OpenAI/Azure OpenAI, Claude, Gemini, Llama, or equivalent models.
  
• Design effective prompt engineering strategies and optimize LLM responses.
  
• Implement document ingestion, chunking, embeddings, retrieval, reranking, and response-generation pipelines.
  
• Develop APIs and AI services using Python and FastAPI/Flask.
  
• Work with Vector Databases such as Pinecone, FAISS, Chroma, Weaviate, or Azure AI Search.
  
• Integrate GenAI solutions with enterprise data sources, applications, databases, and APIs.
  
• Implement LLM evaluation, guardrails, monitoring, security, and responsible AI practices.
  
• Deploy and manage GenAI applications on Azure, AWS, or GCP.
  
• Optimize AI solutions for accuracy, scalability, latency, reliability, and cost.
  
• Collaborate with business stakeholders, architects, data engineers, and AI teams to deliver production-ready solutions.
  

Required Skills

• 4–12 years of overall technology experience with strong hands-on experience in Generative AI.
  
• Strong programming expertise in Python.
  
• Hands-on experience with LLMs, RAG, Prompt Engineering, AI Agents, and Agentic AI.
  
• Experience with LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar frameworks.
  
• Strong understanding of embeddings, vector search, semantic search, and vector databases.
  
• Experience integrating LLM APIs and enterprise data sources.
  
• Experience with Azure OpenAI, AWS Bedrock, Google Vertex AI, or equivalent AI platforms.
  
• Knowledge of FastAPI/Flask, REST APIs, Docker, Git, and CI/CD.
  
• Experience taking GenAI solutions from POC to production.
  
• Strong analytical, debugging, and problem-solving skills.
  

Good to Have

• Experience with LLMOps/MLOps and AI observability.
  
• Knowledge of multi-agent architectures and advanced Agentic AI frameworks.
  
• Experience with fine-tuning, model evaluation, hallucination reduction, and RAG optimization.
  
• Understanding of AI security, data privacy, governance, and responsible AI.