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Job Description
Structured overview of role & requirementsAbout This Role
Lead architecture and delivery of enterprise-grade Generative AI and Agentic AI solutions, ensuring scalable, secure, production-ready deployments.
Own technical vision from discovery, PoC, production deployment to optimization phases.
Design end-to-end GenAI, RAG, multi-agent architectures; define solution patterns including LLMs, embeddings, vector DBs, APIs, data pipelines, and enterprise integrations.
Minimum Requirements
Strong expertise in Generative AI, LLMs, Agentic AI, AI solution architecture, RAG, embeddings, vector search, agent frameworks (e.g., LangChain).
Experience with cloud AI ecosystems: Azure, AWS, or GCP, plus Python, REST APIs, microservices, cloud-native architectures.
Ability to design scalable deployments covering security, privacy, resilience, compliance, and cost optimization.
Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
Experienced architect with demonstrated ability to own AI solution lifecycle from use case ideation to production adoption across enterprise environments.
Operates at intersection of AI research/engineering with strong focus on cloud-native distributed systems and multi-agent orchestration.
Comfortable leading workshops, design reviews, and producing reusable reference architectures and technical standards for GenAI adoption.