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