Principal AI/ML Architect

Evergent; Hyderabad; On-site; INR 2,500,000 - 3,500,000; Full time

Job summary

Evergent is looking for a Principal AI Architect - Conversational AI & LLM Specialist in Hyderabad, India. This critical role will lead the design and implementation of an advanced Agentic AI platform. The successful candidate will shape the conversational AI strategy and mentor junior engineers, ensuring excellence in architectural design and implementation.

This position requires profound technical knowledge, strong programming skills, and a minimum of 10 years of experience in AI/ML development.

Qualifications

• 10+ years of experience in software development with focus on AI/ML and data science.
• Deep expertise in Conversational AI and Large Language Models.
• Strong programming skills in Python.

Responsibilities

• Lead architectural design of an Agentic AI platform.
• Guide the integration of Large Language Models into workflows.
• Collaborate with cross-functional teams and mentor junior engineers.

Skills

Conversational AI

Large Language Models

Software Development

Python

Retrieval Augmented Generation

AI/ML

NLP

Cloud Platforms

Education

Bachelor's degree in Computer Science

Advanced degrees (Master’s or PhD)

Tools

Strands Agents

LangChain

Agent Squad

Amazon Lex

RASA

Job description

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

Summary:

We are seeking an exceptional Principal AIArchitect with deep expertise in Conversational AI and Large Language Models(LLMs) to lead the design and implementation of our next-generation Agentic AIplatform. This role is a critical leadership position responsible forarchitecting, prototyping, and guiding the development of sophisticated agentworkflows that leverage LLMs to solve complex business challenges. You will beinstrumental in shaping our conversational AI strategy, driving innovation, andensuring we remain at the forefront of this rapidly evolving field. This rolerequires a strong blend of technical expertise, architectural vision, andleadership skills.

Responsibilities:

• Architectural Leadership: Designand architect an Agentic AI platform capable of supporting diverse usecases, considering scalability, reliability, security, andmaintainability.
• Agentic AI Platform Development: Guidethe implementation team in developing, testing, and deploying agentworkflows utilizing frameworks such as Strands Agents, Agent Squad, GoogleADK, LangChain, Langgraph, and Langflow.
• LLM Integration & Optimization: Design,implement Proof of Concepts (POCs), and guide the integration of LargeLanguage Models (LLMs) into agent workflows. This includes:
• Prompt Engineering: Developingeffective prompts to elicit desired responses from LLMs.
• Model Grounding: EnsuringLLMs have access to relevant context and data for accurate and reliableperformance.
• Fine-Tuning: Evaluating andimplementing fine-tuning strategies to optimize LLM performance forspecific tasks.
• Retrieval Augmented Generation (RAG) Pipelines: Design, implement POCs, and guide the implementation ofRAG pipelines enabling agents to access and utilize external knowledgesources effectively.
• Vector Database Management: Design,implement POCs, and guide the implementation utilizing vector databases(e.g., Pinecone, Chroma, Weaviate) for efficient storage and retrieval ofembeddings for RAG and semantic search.
• MCP Server Management: Design,implement POCs, and guide the implementation to implement and manage MCPservers to facilitate communication and coordination between agents andLLMs.
• Collaboration & Mentorship: Collaborateclosely with cross-functional teams (engineering, product, data science)to define requirements, prioritize features, and ensure alignment onarchitectural decisions. Mentor junior engineers in best practices forAI/ML development.
• Research & Innovation: Stayabreast of the latest advancements in Conversational AI, LLMs, Agentic AI,and related technologies; proactively identify opportunities forinnovation and experimentation.
• Technical Documentation: Createand maintain comprehensive technical documentation, includingarchitectural diagrams, design specifications, and API documentation.

Qualifications:

• Education: Bachelor's degreein Computer Science or equivalent degree with a strong foundation inAI/ML, NLP, and Data Science. Advanced degrees (Master’s or PhD) arepreferred.
• Experience: 10+ years ofoverall experience in software development with significant exposure toAI/ML, NLP, and data science principles.
• Deep Expertise: Provenexpertise in Conversational AI, Large Language Models (LLMs), and AgenticAI architectures.
• Framework Proficiency: Hands-onexperience with frameworks such as Strands Agents, Agent Squad, GoogleADK, LangChain, Langgraph, and Langflow.
• Platform Experience: Experienceworking with conversational AI platforms like Amazon Lex and RASA.
• LLM Knowledge: Strongunderstanding of various LLMs (e.g., GPT-3/4, PaLM, Llama 2) and theircapabilities.
• RAG Expertise: Solidexperience designing and implementing Retrieval Augmented Generation (RAG)pipelines.
• Vector Database Experience: Practicalexperience with vector databases such as Pinecone, Chroma, or Weaviate.
• Programming Skills: Excellentprogramming skills in Python are essential. Experience with otherlanguages (e.g., Java, Go) is a plus.
• Cloud Proficiency: Experienceworking with cloud platforms (AWS, Azure, GCP).