Technical Lead

Tech lead

Key Responsibilities

• Architect, design, and develop robust and scalable

  Gen AI applications and custom AI Agents

  from concept to deployment.
• Utilize cutting-edge frameworks like

  LangChain

  and

  LangGraph

  to build complex reasoning and orchestration pipelines for multi-step tasks.
• Integrate and fine-tune various Large Language Models (LLMs) and APIs, including those from

  OpenAI

  and

  Google

  .
• Develop efficient data ingestion and retrieval systems, employing techniques like

  Retrieval-Augmented Generation (RAG)

  and managing data within a

  MongoDB

  database.
• Design and manage data schemas and collections in MongoDB, ensuring optimal performance for both structured and unstructured data, including vector embeddings.
• Implement clean, well-documented, and highly performant Python code following best practices for software development.
• Collaborate with cross-functional teams to translate business requirements into technical specifications and deliver innovative solutions.
• Stay current with the latest advancements in Gen AI, machine learning, and the Python ecosystem.
• Contribute to the continuous improvement of our development processes and architecture.

Required Skills & Qualifications

• 5+ years

  of professional experience in Python software development.

• 3+ years

  of hands-on experience in building and deploying Gen AI or machine learning applications.
• Exceptional command of Python, including asynchronous programming (asyncio) and its core libraries and frameworks like fastapi & flask.
• Deep expertise in

  Gen AI concepts

  , including embeddings, vector databases, RAG, and fine-tuning models.
• Extensive experience with

  LangChain

  ,

  LangGraph

  ,

  OpenAI SDK

  , and/or

  Google's Agent Development Kit.

• Proven experience in designing, developing, and optimizing databases with

  MongoDB

  . You should be proficient in schema design, indexing, and using libraries like

  PyMongo

  .
• Strong understanding of MLOps and CI/CD pipelines. Experience with Docker, Kubernetes, and containerized application deployment.
• Practical experience with major cloud platforms such as

  AWS

  ,

  Azure

  , or

  Google Cloud

  , and familiarity with their AI/ML services (e.g., AWS Sagemaker, Vertex AI).
• Solid understanding of RESTful APIs, web services, and microservices architecture.
• Excellent problem-solving skills and a collaborative, team-oriented mindset.

Nice-to-Have Skills

• Experience with other databases, especially vector databases.
• Familiarity with ML model hosting platforms like

  Hugging Face

  .
• Experience with other programming languages or frontend frameworks like

  react

• Contributions to open-source projects, especially in the Gen AI space.