Posted 1mo ago

AI Architect

@ Kumaran Systems
Chennai, Tamil Nadu, India
HybridFull Time
Responsibilities:designing architecture, leading teams, driving pre-sales
Requirements Summary:Extensive experience designing multi-agent AI systems, GenAI, PoC, architecture, and production-grade AI deployments.
Technical Tools Mentioned:Python, Docker, Kubernetes, AWS, Azure, LLMs, Generative AI, Multi-Agent AI, Vector Databases, Agent SDK, NLP, Computer Vision
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Job Description

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

Education: Any Graduate / Post Graduate in Engineering degree or equivalent