GenAI Developer

Role Overview

We are looking for a GenAI Developer to build and integrate AI-powered applications using modern Generative AI technologies. The ideal candidate should have hands-on experience with LLMs, prompt engineering, RAG, Python, and AI/ML frameworks and be comfortable taking AI solutions from concept to production.

Key Responsibilities

- Develop and deploy Generative AI applications using LLMs such as GPT, Claude, Gemini, or open-source models.

- Build RAG (Retrieval-Augmented Generation) pipelines using vector databases and embedding models.

- Design and optimize prompts, prompt templates, and LLM workflows.

- Work with Python and AI/ML frameworks to develop scalable solutions.

- Integrate LLM APIs with existing applications and backend services.

- Work with vector databases such as Pinecone, FAISS, Chroma, or Milvus.

- Develop AI agents, chatbots, document intelligence, and other GenAI use cases.

- Evaluate LLM performance, accuracy, latency, and cost.

- Implement techniques such as fine-tuning, embeddings, function calling, and structured outputs where required.

- Collaborate with product, engineering, and business teams to convert requirements into AI solutions.

- Deploy and monitor GenAI applications in cloud environments such as AWS, Azure, or GCP.

Required Skills

- 2–5 years of experience in Software Development, AI/ML, or GenAI.

- Strong programming skills in Python.





- Hands-on experience with Generative AI and Large Language Models (LLMs).

- Good understanding of RAG, embeddings, vector databases, and prompt engineering.

- Experience with OpenAI, Azure OpenAI, Anthropic, Gemini, or similar LLM APIs.

- Experience with frameworks such as LangChain, LlamaIndex, LangGraph, or Semantic Kernel.

- Understanding of REST APIs, JSON, Git, and backend development.

- Familiarity with cloud platforms such as AWS, Azure, or GCP.

- Good understanding of AI application development and software engineering best practices. Good to Have

- Experience building AI Agents, Agentic AI workflows.

- Knowledge of LLM evaluation and observability tools.

- Experience with Docker and Kubernetes.

- Exposure to CI/CD and MLOps, LLMOps.

- Knowledge of fine-tuning or open-source models such as Llama, Mistral, or Qwen.

- Experience working with enterprise data, APIs, and document-processing pipelines. Soft Skills

- Strong problem-solving and analytical skills.

- Good communication and collaboration abilities.

- Ability to work in a fast-paced product, startup environment.

- Robust ownership and willingness to experiment with emerging AI technologies. Education

- Bachelor’s or Master’s degree in Computer Science, Engineering, AI/ML, or a related field.

Location

Bangalore, Karnataka, India

📌 AI Developer (Bengaluru)
🏢 MetAntz
📍 Bengaluru