AI Solutions Architect

Job Description

The AI Solutions Architect role involves owning AI solutions technically and driving end-to-end from stakeholder interaction, conceptualization, PoC, to productionization. It requires driving quick Proof of Concept / Feasibility, supporting pre-sales proposals and customer engagement, creating technical artifacts for the solution, driving the solution to maturity and production-grade readiness through the team, and staying up-to-date with technology trends to apply appropriately in solutions.

Requirements

Key Skills

1. Experience in Multi-Agent AI system design & development for business problems with standard Agent SDK, A2A, MCP
2. Experience in GenAI solutions design & development like RAG, Agentic RAG, Vector DB, Agentic Patterns Orchestrator, Planner.
3. Experience in fine-tuning various LLMs like Mistral, Olama with domain data.
4. Experience in designing evaluation & AgentOps for Agentic AI solutions.
5. Experience in training ANN for NLP, Computer Vision problems with Object Detection Models, Transformer Models, Prediction Models.
6. Strong Python system design & development, microservices, docker, Kubernetes, AWS / Azure