AI Architect – Generative AI, Enterprise Solutions

• Drive the end-to-end architecture and technical visionfor generative AI within the function – reference architectures, patterns, and standards that teams build against.
• Make authoritative technology decisions,selecting the right models, frameworks, and agent harnesses for each use case, balancing capability, latency, cost, and risk.
• Move solutions from proof-of-concept to production with realistic, production-grade designs – covering orchestration, retrieval (RAG), evaluation, observability, guardrails, and human-in-the-loop.
• Integrate GenAIinto the existing cloud solutions and automation platform (AWS, CI/CD toolchain, ITSM) so GenAI is a first-class, governed capability.
• Design for scale and operational excellencefor GenAI workloads – throughput, latency, reliability, and cost optimization (token economics, caching, model routing).
• Establish the operational foundationincluding evaluation pipelines, monitoring, drift/quality management, and incident response for Agentic solutions.
• Bake in guardrailssuch as security, data privacy, responsible-AI, hallucination mitigation, and regulatory compliance into every architecture.
• Advise and influenceto CXO-level leaders, translating complex AI concepts into clear business value, trade-offs, risks, and roadmaps.
• Shape the generative-AI strategy and roadmapfor the enterprise, aligning technology investment with business outcomes and priorities.
• Build and presentbusiness cases, ROI, and build-vs-buy analyses for AI initiatives.
• Serve as an evangelist and trusted expert– to executives, engineering teams, and external partners – and champion an enterprise AI vision.
• Mentor and upskillengineering teams and set architecture governance, review gates, and reusable building blocks.
• Define and stewardAI governance, standards, and best practices in partnership with security, data, and legal.

• Bachelor's or Master's degreein Computer Science, Engineering, or a related field – or equivalent practical experience.
• 10+ years of experience in software/AI engineering and architecture, including senior technical leadership on large-scale systems.
• Recognized depthin generative AI: LLMs, prompt/context engineering, RAG, agent frameworks (e.g., Lang Chain, Amazon Bedrock Agents), and agent harnesses.
• Proven track record designing and running GenAI solutions in production at scale – including evaluation, observability, cost, and reliability.
• Deep hands-on knowledge of AWS and its AI services (e.g., Amazon Bedrock), plus core cloud infrastructure (compute, networking, IAM, containers).
• Strong groundingwith enterprise architecture practices, integration, and the modern Dev Ops toolchain (Git Hub, Jenkins, Artifactory, Sonar Qube).
• Exceptional communication and executive-presence skills – able to hold credible, persuasive CXO-level conversations and articulate complex technology in business terms.
• Solid understanding of responsible-AI, security, and data-governance considerations for enterprise AI.

Demonstrates expertise in generative AI architecture and implementation, with a strong focus on AWS cloud solutions, operational excellence, and AI governance. Capable of translating complex AI concepts into business value while mentoring engineering teams and influencing executive leadership.

• Generative AI Architecture
• AWS AI Services
• Large-Scale Systems Design
• AI Governance and Compliance
• Executive Communication

• Generative AI
• LLMs
• Prompt Engineering
• RAG
• Agent Frameworks
• Production-Grade Design
• Cost Optimization
• Evaluation Pipelines
• Monitoring and Incident Response
• Data Privacy

• Exceptional Communication
• Executive Presence
• Mentoring

• Bachelor's Degree in Computer Science
• Master's Degree in Engineering

• AI Engineering
• Enterprise Architecture
• Dev Ops
• Security
• Data Governance

• AWS
• Git Hub
• Jenkins
• Artifactory
• Sonar Qube