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.
- Strong 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
