AI Architect

Role Overview 

We are looking for a highly experienced Senior AI
Solutions Architect / AI Lead to design and deliver advanced AI and
Generative AI solutions for complex business problems. This role requires
strong expertise in multi -agent AI architectures, GenAI frameworks, and
production -grade AI systems.

The ideal candidate will lead the end -to -end
lifecycle of AI solutions—from stakeholder discussions and
conceptualization to Proof of Concept (PoC), architecture design, and
deployment at scale. The role also involves supporting pre -sales activities,
guiding engineering teams, and ensuring solutions are robust, scalable, and
production -ready.

Work Location: Chennai (Hybrid) – 3 days at office
and 2 days at home (11 AM – 8 PM)

Key Responsibilities

• Own
  and drive AI solution architecture and delivery from stakeholder
  engagement and ideation through PoC development and full -scale production
  deployment.
  
• Collaborate
  with business stakeholders to understand requirements, identify
  opportunities, and design AI -driven solutions.
  
• Rapidly
  build Proof of Concepts (PoC) and feasibility prototypes to
  validate technical approaches and business value.
  
• Support pre -sales initiatives, including solution proposals, architecture
  presentations, and customer engagements.
  
• Design
  and produce technical solution artifacts such as architecture
  documents, design specifications, and implementation guidelines.
  
• Lead
  engineering teams to build, scale, and productionize AI solutions using modern AI/ML frameworks and cloud platforms.
  
• Establish
  best practices for AI system architecture, governance, monitoring, and
  evaluation.
  
• Drive
  innovation by tracking emerging AI/ML technologies and integrating
  relevant advancements into solutions.
  
• Mentor
  technical teams and ensure the adoption of scalable, maintainable, and
  high -quality engineering practices.
  

Key Skills & Technical Expertise

AI & Generative AI

• Hands -on
  experience designing and developing Multi -Agent AI systems to solve
  complex business problems.
  
• Experience
  with Agent frameworks and protocols including Agent SDK, A2A
  (Agent -to -Agent), and MCP (Model Context Protocol).
  
• Expertise
  in Generative AI solution architecture, including:
  
• Retrieval -Augmented
  Generation (RAG)
  
• Agentic
  RAG
  
• Vector
  Databases
  
• Agentic
  Patterns (Planner, Orchestrator, Tool Use, Multi -Agent Collaboration)
  

Large Language Models

• Experience
  with fine -tuning and customizing LLMs such as Mistral,
  Ollama -based models, or similar open -source models using
  domain -specific datasets.
  
• Strong
  understanding of prompt engineering, LLM optimization, and evaluation
  frameworks.
  

AI System Evaluation & Operations

• Experience
  in designing evaluation frameworks and AgentOps pipelines for
  monitoring, optimizing, and managing Agentic AI systems in production.
  

Machine Learning & Deep Learning

• Experience
  building and training Artificial Neural Networks (ANNs) for:
  
• Natural
  Language Processing (NLP)
  
• Computer
  Vision
  
• Predictive
  modeling
  
• Hands -on
  experience with Object Detection models, Transformer architectures, and
  predictive ML models.
  

Software Engineering &
Infrastructure

• Strong Python development and system design expertise.
  
• Experience
  building scalable microservices architectures.
  
• Hands -on
  experience with Docker and Kubernetes for containerization and
  orchestration.
  
• Experience
  deploying and managing AI workloads on cloud platforms such as AWS or
  Azure