Gen AI Architect

GenAI design, architecture & development
•    Define end-to-end GenAI/AI strategy and technical architecture, aligning solutions with business objectives, security, and scalability requirements.
•    Design and develop applications using GenAI LLMs (GPT, Claude, Llama, Mistral, etc ).
•    Define end-to-end GenAI/AI strategy and technical architecture, aligning solutions with business objectives, security, and scalability requirements.
•    Work with different python packages – Langchain, LangGraph, Streamlit, Numpy, Pandas, Scikit Learn, Transformers.
•    Design and implement Retrieval-Augmented Generation (RAG) pipelines and work with vector databases (e.g., Pinecone, Weaviate, Chroma) to enhance model accuracy.
•    Optimize prompt engineering techniques—including chain-of-thought, tool calling, and guardrails—to improve AI reliability.
•    Deploy, optimize, and monitor GenAI models in cloud environments (AWS, Azure, or GCP) using containerization (Docker, Kubernetes).
•    Create back end APIs using FastAPI.

Software Testing
•    Should have experience on software testing and knowledge on the different phases of software testing.
•    Should have experience or knowledge on the different test automation frameworks – java selenium, python selenium, playwright, etc.
•    Should have experience on performing LLM validation using frameworks like EVALS, RAGAS for correctness, hallucination detection, reliability, and performance benchmarking.

Documentation & Reporting
•    Prepare and maintain detailed architecture diagrams and development plans 
•    Report development progress to stakeholders

Good to have 
•    Front end development experience using ReactJS
 
Required Skills & Qualifications
•    Bachelor’s or Master’s degree in Computer Science Engineering, or a related field.
•    Proficiency in programming languages such as Python.
•    Experience on designing and developing GenAI solutions using Cloud hyperscalers(AWS Bedrock, Google Vertex AI, Azure AI Foundry) services.
•    Experience in developing RAG based GenAI applications. Should have worked with any of the Vector Databases – Pinecone, ChromaDB, FAISS, etc.
•    Good understanding of SDLC, STLC, agile methodologies, and DevOps practices.
•    Strong analytical, problem-solving, and communication skills.