The role combines solution architecture leadership with deep expertise in GenAI application design, agentic systems, and AI cloud architecture on AWS and Snowflake....Agentic AI Architecture
• Design enterprise agentic AI solutions leveraging multi-agent orchestration, tool invocation, memory, planning, reasoning flows, and human-in-the-loop control mechanisms.
• Establish design guardrails, evaluation frameworks, monitoring approaches, and observability standards for agent behavior in production.
• Integrate agent-based systems with enterprise APIs, structured and unstructured data platforms, workflow engines, and knowledge sources.
• Drive architecture decisions around scalability, resilience, security, governance, and operational control for agent-based applications....Productionization, Engineering & Governance
• Collaborate with Data Engineering, Platform Engineering, DevOps, and Security teams to productionize AI and GenAI solutions in scalable cloud environments.
• Design CI/CD and automation patterns for model deployment, prompt/version management, testing, release control, and operational support.
• Implement monitoring for model drift, prompt drift, performance degradation, usage patterns, system health, and data integrity.
• Support governance, risk management, and responsible AI initiatives by embedding security, privacy, compliance, and auditability into solution design.
• Innovation & Technical Leadership
• Stay current with advancements in foundation models, multimodal AI, agent frameworks, orchestration patterns, and cloud-native AI services.
• Provide architecture guidance, design reviews, and technical mentorship across cross-functional teams.
• Contribute to enterprise-wide AI best practices, reusable frameworks, and...Qualifications & Experiences:
• Bachelor's degree, Master's degree, or higher in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related quantitative discipline.
• 8+ years of relevant experience in solution architecture, data science, machine learning, or AI engineering, with at least 2+ years of experience in Generative AI / LLM-based solutions.
• Demonstrated track record of designing and delivering production-grade AI/ML/GenAI solutions with measurable business impact.
• Strong experience in architecting enterprise AI solutions across business workflows, data ecosystems, and cloud platforms.
• Hands-on expertise in building and scaling GenAI and LLM applications, including prompt engineering, RAG architectures, semantic search, embeddings, and evaluation frameworks.
• Experience designing or supporting agentic AI systems, including orchestration, tool usage, memory, guardrails, and human oversight patterns.
• ...Key Technical Skills & Expertise
• Hands-on experience designing and deploying Generative AI and agentic AI solutions using large language models via AWS Bedrock Agents, enterprise LLM platforms, or foundation models
• Strong proficiency in prompt engineering, structured output design, few-shot prompting, and systematic prompt optimization for agent-driven workflows
• Experience building Retrieval-Augmented Generation (RAG) pipelines that integrate vector search with enterprise knowledge bases and APIs
• Deep familiarity with embedding models, semantic search, and vector stores, including OpenSearch vector search and equivalent technologies
• Practical experience implementing multi-agent architectures, including planning, tool usage, memory management, and human-in-the-loop control patterns using frameworks such as LangGraph, CrewAI, or AutoGen
• Understanding of LLM and agent evaluation methodologies, including hallucination detection, response quality scoring, safe