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High — PwC brand, Bengaluru metro, mid-level generalist role, and broad, popular GenAI skill requirements.
Medium — GenAI engineering skills transfer across industries, though enterprise consulting and governance add specificity.
High due to explicit 5–8 years, mandatory GenAI experience, and extensive required tech stack.
Architect and lead enterprise-scale Generative AI and Agentic AI solutions including multi-agent systems, RAG architectures, AI copilots, and AI workflow automation platforms.
Lead end-to-end AI product development lifecycle from ideation to production deployment and establish AI engineering standards, evaluation frameworks, and governance.
Collaborate with clients and cross-functional teams (Data Engineering, Cloud, Cyber, Business) to define AI strategy, use cases, roadmaps, and deliver integrated AI solutions.
4+ years of total work experience; 5-8 years technology experience with 3+ years specifically in GenAI / Large Language Model engineering.
Bachelor of Technology (BE/B.Tech) degree required.
Strong expertise and hands-on experience with LLMs, Agentic AI, RAG frameworks, prompt engineering, AI governance, and vector databases.
Technical experience with LangChain, LangGraph, AutoGen, CrewAI, Azure OpenAI, OpenAI, Anthropic Claude, Gemini, Azure, AWS, GCP, MLflow, Databricks, Fabric, Kubernetes, and Python software engineering.
Experienced AI engineer with deep knowledge in Generative AI, foundation models, and enterprise AI platform development.
Proven capability in leading architecture, design reviews, and mentoring engineering teams in AI technologies.
Comfortable working directly with clients to shape AI strategies and collaborate across technical and business domains.