Job Description

Job Description

REQUIREMENTS:

  • Total experience 10+ years.
  • Deep understanding of LLMs (., 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 (., 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 (., Azure Machine Learning Studio, AI Foundry).
  • Strong understanding of vector databases (., Weaviate, Neo4j)
  • understanding of GenAI evaluation metrics (., 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.
  • Should be able to build & deploy AI pipelines using SageMaker, Vertex AI, or Azure ML
  • Hands on Docker, Kubernetes, and CI/CD pipelines (GitHub Actions, Argo) for scalable AI infra
  • Hands-on with serverless AI APIs, containerized model serving, and GPU orchestration
  • Experience with IaC (Terraform / Bicep) and cloud monitoring tools
  • Data pipelines via Airflow, Kafka, or Databricks
  • 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 one production GenAI/Agentic AI solution.
  • Must have proficiency with FastAPI and at least one ORM (., SQLAlchemy, Tortoise ORM).
  • Should have experience 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

    • RESPONSIBILITIES:

  • 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.

    • Qualifications

    Bachelor’s or master’s degree in computer science, Information Technology, or a related field.

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