Job Title: Principal AI Architect - Conversational AI & LLM Specialist

Location: Hyderabad, India

Summary:

We are seeking an exceptional Principal AI Architect with deep expertise in Conversational AI and Large Language Models (LLMs) to lead the design and implementation of our next-generation Agentic AI platform. This role is a critical leadership position responsible for architecting, prototyping, and guiding the development of sophisticated agent workflows that leverage LLMs to solve complex business challenges. You will be instrumental in shaping our conversational AI strategy, driving innovation, and ensuring we remain at the forefront of this rapidly evolving field. This role requires a strong blend of technical expertise, architectural vision, and leadership skills.

Responsibilities:

• Architectural Leadership: Design and architect an Agentic AI platform capable of supporting diverse use cases, considering scalability, reliability, security, and maintainability.
• Agentic AI Platform Development: Guide the implementation team in developing, testing, and deploying agent workflows utilizing frameworks such as Strands Agents, Agent Squad, Google ADK, LangChain, Langgraph, and Langflow.
• LLM Integration & Optimization: Design, implement Proof of Concepts (POCs), and guide the integration of Large Language Models (LLMs) into agent workflows. This includes:
• Prompt Engineering: Developing effective prompts to elicit desired responses from LLMs.
• Model Grounding: Ensuring LLMs have access to relevant context and data for accurate and reliable performance.
• Fine-Tuning: Evaluating and implementing fine-tuning strategies to optimize LLM performance for specific tasks.
• Retrieval Augmented Generation (RAG) Pipelines: Design, implement POCs, and guide the implementation of RAG pipelines enabling agents to access and utilize external knowledge sources effectively.
• Vector Database Management: Design, implement POCs, and guide the implementation utilizing vector databases (e.g., Pinecone, Chroma, Weaviate) for efficient storage and retrieval of embeddings for RAG and semantic search.
• MCP Server Management: Design, implement POCs, and guide the implementation to implement and manage MCP servers to facilitate communication and coordination between agents and LLMs.
• Collaboration & Mentorship: Collaborate closely with cross-functional teams (engineering, product, data science) to define requirements, prioritize features, and ensure alignment on architectural decisions. Mentor junior engineers in best practices for AI/ML development.
• Research & Innovation: Stay abreast of the latest advancements in Conversational AI, LLMs, Agentic AI, and related technologies; proactively identify opportunities for innovation and experimentation.
• Technical Documentation: Create and maintain comprehensive technical documentation, including architectural diagrams, design specifications, and API documentation.

Qualifications:

• Education: Bachelor's degree in Computer Science or equivalent degree with a strong foundation in AI/ML, NLP, and Data Science. Advanced degrees (Master’s or PhD) are preferred.
• Experience: 10+ years of overall experience in software development with significant exposure to AI/ML, NLP, and data science principles.
• Deep Expertise: Proven expertise in Conversational AI, Large Language Models (LLMs), and Agentic AI architectures.
• Framework Proficiency: Hands-on experience with frameworks such as Strands Agents, Agent Squad, Google ADK, LangChain, Langgraph, and Langflow.
• Platform Experience: Experience working with conversational AI platforms like Amazon Lex and RASA.
• LLM Knowledge: Strong understanding of various LLMs (e.g., GPT-3/4, PaLM, Llama 2) and their capabilities.
• RAG Expertise: Solid experience designing and implementing Retrieval Augmented Generation (RAG) pipelines.
• Vector Database Experience: Practical experience with vector databases such as Pinecone, Chroma, or Weaviate.
• Programming Skills: Excellent programming skills in Python are essential. Experience with other languages (e.g., Java, Go) is a plus.
• Cloud Proficiency: Experience working with cloud platforms (AWS, Azure, GCP).