GenAI Solution Architect

Overview

The GenAI Solution Architect is a key member of the AI R&D team, responsible for designing and delivering advanced AI solutions leveraging LLMs, RAG, agentic architectures, and orchestration frameworks. The role provides technical leadership, accelerates knowledge transfer, and mentors internal engineers.

Key Responsibilities

• Design and implement scalable GenAI solutions for business use cases.
• Lead development of agentic and orchestrated multi-agent architectures.
• Collaborate with ML engineers to integrate models with enterprise data pipelines.
• Partner with process automation engineers to enhance RPA with AI capabilities.
• Provide technical mentorship to process automation engineers, accelerating AI skill development.
• Work with external consultants to ensure alignment and knowledge transfer.

Key Performance Indicators (KPIs

• Delivery of GenAI-based pilots and solutions within agreed timelines.
• Successful integration of agentic AI into at least two core business processes in year one.
• Measurable uplift in AI capability of process automation engineers.
• Positive stakeholder feedback on technical quality and scalability of solutions.

Skills & Qualifications

• Master's degree in Computer Science, Engineering, or related field.
• Hands-on experience with LLMs, RAG, and multi-agent architectures.
• Proven track record in building production-ready AI solutions.
• Strong mentoring and technical leadership skills.
• Demonstrated experience with modern LLM and GenAI frameworks (e.g., Hugging Face, LangChain, LlamaIndex), agent orchestration tools (e.g., LangGraph, AutoGen, CrewAI), workflow automation tools (e.g., n8n, PowerAutomate) and deployment environments (e.g., Azure OpenAI, AWS Bedrock, GCP Vertex AI).