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Tier-1 brand, metro locations, mid-level generalist GenAI skills amplify candidate competition.
Specialized GenAI, agent frameworks and vector DBs increase domain bias but remain partially transferable.
Mandatory GenAI architecture, production cloud deployment, and >5 years make filtering strict.
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Design, architect, and implement GenAI solutions using RAG, agent frameworks, reusable components/APIs, and MCP server.
Deploy GenAI solutions in production on platforms like AWS, Azure, Google Cloud, or Snowflake.
Lead lifecycle management of GenAI solutions focusing on innovation, sustainability, and operational excellence while managing stakeholders and cross-functional communication.
Bachelor’s degree.
More than 5 years experience in solution architecture focused on generative AI, agent-based systems, and business consulting for GenAI.
Strong software engineering skills for building and operating GenAI solutions.
Production deployment experience on at least one of AWS, Azure, Google Cloud, or Snowflake.
Experienced in consulting on business and technical requirements for GenAI and agent solution projects.
Skilled in architecting scalable GenAI platforms integrating LLMs, agent frameworks (e.g. LangGraph, ADK), and vector databases.
Capable of mentoring teams and effectively communicating complex GenAI concepts to both technical and business audiences.