Enterprise AI Architect

Job Title: Enterprise AI Architect

Experience: 20 years overall 10 years in Architecture 5 years in AI/ML solutioning

3 years in CPG or Retail domain across the value chain (Manufacturing PLM Supply Chain Logistics Sales Marketing)

1. Role Summary

We are seeking a hands-on Enterprise AI Architect to lead the design development and governance of AI solutions across multiple accounts in RCG North America. This role will drive the enterprise AI architecture strategy-evaluating and enhancing frameworks designing scalable and secure AI-native and agentic solutions and ensuring alignment with business objectives across the CPG/Retail value chain. The ideal candidate will demonstrate deep technical expertise in GenAI LLMs and agentic workflows and will be responsible for driving both business transformation and IT service delivery transformation using AI across a portfolio of projects. The candidate will also collaborate with cross-functional teams drive innovation scout emerging AI technologies and startups and foster a culture of experimentation and co-innovation with clients and partners.

1. Key Responsibilities
   1. AI Strategy & Architecture

• Evaluate existing AI frameworks platforms and governance models to identify strengths weaknesses and gaps
• Align AI initiatives with business objectives data governance and IT infrastructure.
• Stay updated on emerging AI technologies and recommend adoption strategies evaluate and recommend AI platforms tools and frameworks.
• Recommend enhancements to AI architecture tools and integration strategies.
• Demonstrate measurable ROI from AI initiatives including cost savings revenue uplift and efficiency gains.
  1. AI Solution Design
• Create end to end AI reference architectures covering data models agentic workflows orchestration security and observability aligned to enterprise standards
• Agentic Flow Architectures for business workflow transformations & autonomous task execution use cases
• Architect and Design AI Agents for AIOps / Intelligent Operations
• Collaborate with engineering and operations teams to integrate AI solutions into enterprise systems
  1. Governance & Compliance
• Ensure compliance with enterprise AI governance security and ethical standards.
• Establish best practices for responsible AI and model explainability
• Establish observability standards including tracing logging and performance monitoring

1. Desired Candidate Profile
   1. Required AI Technology Skills

• Strong knowledge of AI/ML platforms & technologies cloud services (Azure GCP) and enterprise architecture principles
• LLM Expertise: Strong understanding of large language models (OpenAI Anthropic Gemini LLaMA) and their integration
• Prompt Engineering: Designing reusable prompts guardrails and system instructions
• Knowledge Retrieval: Proficiency in embedding models and vector DBs (Pinecone Weaviate Chroma) RAG / GraphRAG
• Agentic AI: Proven experience designing agentic workflows using frameworks like LangChain / LangGraph managing state and memory integrating external tools/APIs and building and leveraging MCP tools
• Observability: Experience with tracing logging and performance monitoring of Gen AI solution using frameworks like LangFuse Arize Phoenix or similar
• MLOps / LLMOps: Familiarity with CI/CD for models prompt versioning and model lifecycle management
• Security & Governance: Implement AI governance compliance and responsible AI practices.
• Proven experience of using AI across the IT service delivery lifecycle both engineering and operations using tools like GitHub Copilot Claude Code Cursor MCP servers custom agents
  1. Required Architecture Skills

• Experience in architecting and designing applications with different architecture patterns across web microservices APIs event-driven data containerized cloud-native cloud-agnostic AI/ML
• Identifying NFRs architecting for NFR compliance and validating the same
• Experience of having worked on different technology stacks such as Python and/or Java
• Good experience with traditional relational databases as well as with NoSQL databases including data modeling activities
• Backend integration using APIs / ESB / Middleware / message-oriented systems and using data exchange formats such as JSON XML
• Good experience on at least one of the public clouds such as Azure and GCP (or AWS) including experience in architecting cloud-native solutions
  1. Leadership & Soft Skills
• Experience providing architectural and technology leadership across a portfolio of projects / programs not limited to a single initiative.
• Proven ability to lead participate in and drive consulting workshops and engagements with diverse client stakeholders partners and vendors. Should have the ability to influence decision making.
• Pre-sales experience including technical solutioning estimation proposal development and client presentations.
• Proficient in articulation communication and presentation including to CXO-level client stakeholders.
• Ability to evaluate and recommend emerging AI technologies startups and partners for enterprise adoption and drive co-solutioning initiatives.
• Track record of driving innovation thought leadership and co-innovation with customers.
• Demonstrated experience leading large multi-regional teams (onsite/offshore) mentoring technical leaders and navigating complex organizations.
• High learning agility adaptability strategic thinking and strong problem-solving skills.