AI Lead

Job Summary

We are seeking a highly skilled and motivated AI/ML Engineer specializing in Agentic AI to join our dynamic team. The ideal candidate will have a strong foundation in machine learning and a passion for building intelligent, autonomous agents. You will be responsible for designing, developing, and deploying sophisticated AI agents that can perform complex tasks, interact with their environment, and make intelligent decisions. This role will involve working with state-of-the-art large language models (LLMs) and agentic frameworks to create next-generation AI systems.

Key Responsibilities

• Design and Develop AI Agents:

  Architect, build, and maintain autonomous AI agents capable of complex reasoning, planning, and tool use.

• LLM Integration and Fine-Tuning:

  Leverage and fine-tune large language models (LLMs) from providers like OpenAI, Google, and open-source alternatives to serve as the core of our AI agents.

• Framework Implementation:

  Utilize agentic AI frameworks such as LangChain, AutoGen, and CrewAI to structure and develop agentic workflows.

• Tool and API Integration:

  Develop and integrate tools and APIs to enable AI agents to interact with various data sources and external systems.

• Data and Knowledge Management:

  Implement and manage vector databases and knowledge graphs to provide agents with long-term memory and contextual understanding.

• Prototyping and Iteration:

  Rapidly prototype and iterate on new agentic AI concepts and applications.

• Collaboration:

  Work closely with cross-functional teams, including product managers, software engineers, and data scientists, to deliver high-quality AI solutions.

• Stay Current:

  Keep abreast of the latest advancements in agentic AI, LLMs, and machine learning to drive innovation within the company.

Required Qualifications

• Bachelors degree in computer science, Artificial Intelligence, a related technical field, or equivalent practical experience.
• Proven experience in designing and developing AI/ML models and systems.
• Strong programming skills in Python and familiarity with common machine learning libraries such as TensorFlow, PyTorch, and scikit-learn.
• Hands-on experience with large language models (LLMs) and related concepts like prompt engineering and fine-tuning.
• Familiarity with agentic AI concepts and frameworks (e.g., LangChain, AutoGen).
• Experience with data storage and retrieval systems, including vector databases (e.g., Pinecone, Weaviate).

Solid understanding of software development best practices, including version control (Git), testing, and CI/CD.