- Total experience: 6+ years.
- Deep understanding of LLMs (e.g., GPTs, Llama, Claude, Gemini, Qwen, Mistral, BERT-family models) and their architectures (Transformers)
- Should have expert-level prompt engineering skills and proven experience implementing RAG patterns
- High proficiency in Python and standard AI/ML libraries (e.g., LangChain, LlamaIndex, LangGraph, LangSmith, Hugging Face Transformers, Scikit-learn, PyTorch/TensorFlow).
- Experience implementing RAG architectures and prompt engineering.
- Strong experience with fine-tuning and distillation techniques and evaluation.
- Strong experience using managed AI/ML services on the target cloud platform (e.g., Azure Machine Learning Studio, AI Foundry).
- Strong understanding of vector databases (e.g., Weaviate, Neo4j)
- understanding of GenAI evaluation metrics (e.g., BLEU, ROUGE, perplexity, semantic similarity, human evaluation).
- Architect and implement scalable GenAI and Agentic AI solutions end-to-end.
- Should be able to write high-quality, production-ready Python code with strong testing and maintainability practices.
- Should be able to productionize AI systems on Azure or AWS, ensuring enterprise-grade reliability and performance.
- Should be able to build and expose APIs using FastAPI, integrating with databases through an ORM.
- Should be able to scale GenAI solutions to support enterprise workloads.
- Collaborate across product and engineering teams to convert business needs into AI-driven solutions.
- Strong ability to both architect and code GenAI/Agentic AI solutions.
- Proven production experience with GenAI deployments on Azure or AWS.
- Strong experience in scaling AI solutions in live environments.
- Very strong Python programming skills with a track record of clean, efficient, and maintainable code.
- Should have successfully delivered at least production GenAI/Agentic AI solution.
- Must have proficiency with FastAPI and at least ORM (e.g., SQLAlchemy, Tortoise ORM).
- Should have familiarity with Model Context Protocol (MCP).
- Should have contributions to open-source GenAI projects.
- Good to have experience with React (or some other JS frameworks) for building user-facing interfaces and front-end integrations
- Excellent communication skills and the ability to collaborate effectively with cross-functional teams.
- Understanding the client’s business use cases and technical requirements and be able to convert them into technical design which elegantly meets the requirements.
- Mapping decisions with requirements and be able to translate the same to developers.
- Identifying different solutions and being able to narrow down the best option that meets the clients’ requirements.
- Defining guidelines and benchmarks for NFR considerations during project implementation.
- Writing and reviewing design document explaining overall architecture, framework, and high-level design of the application for the developers.
- Reviewing architecture and design on various aspects like extensibility, scalability, security, design patterns, user experience, NFRs, etc., and ensure that all relevant best practices are followed.
- Developing and designing the overall solution for defined functional and non-functional requirements; and defining technologies, patterns, and frameworks to materialize it.
- Understanding and relating technology integration scenarios and applying these learnings in projects.
- Resolving issues that are raised during code/review, through exhaustive systematic analysis of the root cause, and being able to justify the decision taken.
- Carrying out POCs to make sure that suggested design/technologies meet the requirements.
Bachelor’s or master’s degree in computer science, Information Technology, or a related field.
