AI Engineer

Job Title: AI Engineer (GCC) (Chennai/ Bengaluru/ Hyderabad / Gurgaon)-India.

***Please note the location of these roles. Do not apply if you are not open for relocation to India***

Responsibilities:

Design, Develop, and Deploy AI Agents: Utilize frameworks like LangGraph and LangChain to enable complex task automation and conversational workflows.

Integrate and Fine-tune Models: Work with state-of-the-art models, including OpenAI's o1/o3, Google's Gemini, and Meta's Llama 4, for applications such as text generation, image creation, and code synthesis.

Implement Multi-Agent Systems: Leverage protocols like Anthropic's Model Context Protocol (MCP) and Google's Agent2Agent (A2A) to facilitate inter-agent communication across different platforms.

Develop Memory-Augmented Systems: Utilize long-context models and retrieval-augmented generation (RAG) techniques to enhance AI capabilities.

Collaborate with Cross-Functional Teams: Work closely with data scientists, software engineers, and product managers to bring AI solutions from concept to production.

Stay Abreast of Advancements: Keep up with the latest advancements in AI/ML and contribute to the team's knowledge base and best practices.

Qualifications:

Educational Background: Bachelor's degree or higher in Computer Science, Engineering, Mathematics, Statistics, or a related field.

Experience with AI Frameworks and Tools: Proficiency with modern AI frameworks and tools, including LangGraph, LangChain, LlamaIndex, and Semantic Kernel.

Technical Skills: Proficiency in Python and familiarity with libraries such as PyTorch, Pandas, and NumPy.

Hands-on Experience with LLMs and SLMs: Experience with large language models (LLMs) and small language models (SLMs), including OpenAI's o1/o3, Google's Gemini, and Meta's Llama 4.

Understanding of Multi-Agent Systems: Knowledge of multi-agent systems and protocols like MCP for server tooling, A2A for agent communication, short- and long-term memory.

Familiarity with MLOps Practices: Experience with MLOps practices, CI/CD pipelines, and cloud platforms such as Databricks and Snowflake.

Problem-solving skills: Strong problem-solving skills and the ability to work both independently and collaboratively.