Description

Position Overview

We are seeking an experienced AI Architect to lead the design, development, and deployment of enterprise-scale Artificial Intelligence and Generative AI solutions. The ideal candidate will possess deep expertise in modern Large Language Models (LLMs), multi-cloud AI platforms, and enterprise architecture, with proven hands-on experience leveraging Anthropic Claude, Google Gemini, Microsoft Azure AI Services, and AWS AI/ML services.

This role will partner with business leaders, engineering teams, data scientists, and cloud architects to define AI strategy, establish architecture standards, and deliver scalable, secure, and responsible AI solutions that drive measurable business outcomes.

Key Responsibilities

AI & GenAI Architecture

     •     Define and implement enterprise AI architecture frameworks, standards, and best practices.

     •     Design end-to-end Generative AI solutions leveraging Claude, Gemini, OpenAI, and other leading foundation models.

     •     Architect Retrieval Augmented Generation (RAG), agentic AI, multi-agent systems, vector databases, and knowledge management solutions.

     •     Develop scalable AI platforms supporting enterprise-wide adoption and governance.

Cloud & Platform Architecture

     •     Architect AI solutions across Azure and AWS environments.

     •     Design secure and scalable AI infrastructure utilizing:

     ◦     Azure OpenAI Service

     ◦     Azure AI Foundry

     ◦     Azure Machine Learning

     ◦     Azure Cognitive Services

     ◦     Amazon Bedrock

     ◦     Amazon SageMaker

     ◦     AWS AI Services

     •     Establish cloud-native patterns for AI application deployment and operations.

Solution Design & Delivery

     •     Lead technical architecture reviews and solution design workshops.

     •     Translate business requirements into scalable AI and machine learning solutions.

     •     Collaborate with engineering teams to implement production-grade AI systems.

     •     Drive AI adoption through reusable frameworks, accelerators, and reference architectures.

Governance & Responsible AI

     •     Define AI governance, security, compliance, and risk management frameworks.

     •     Implement model monitoring, observability, guardrails, and responsible AI practices.

     •     Ensure solutions comply with enterprise security, privacy, and regulatory requirements.

Leadership & Innovation

     •     Serve as a trusted advisor to executive leadership on AI strategy and emerging technologies.

     •     Mentor architects, engineers, and data science teams.

     •     Evaluate emerging AI technologies and recommend adoption strategies.

     •     Drive innovation initiatives and proof-of-concepts for strategic business opportunities.

Required Qualifications

Experience

     •     10+ years of experience in software engineering, cloud architecture, data platforms, or enterprise architecture.

     •     5+ years of experience designing and implementing AI/ML solutions.

     •     3+ years of experience with Generative AI and Large Language Models in enterprise environments.

     •     Proven experience leading enterprise AI transformations and architecture programs.

Technical Expertise

Foundation Models & GenAI

     •     Demonstrated expertise with:

     ◦     Anthropic Claude

     ◦     Google Gemini

     ◦     OpenAI models

     ◦     Multi-model orchestration strategies

     •     Experience with prompt engineering, fine-tuning, model evaluation, and AI agent frameworks.

Microsoft Azure

     •     Azure OpenAI Service

     •     Azure AI Foundry

     •     Azure Machine Learning

     •     Azure Kubernetes Service (AKS)

     •     Azure Data Services

     •     Azure Security and Identity solutions

Amazon Web Services

     •     Amazon Bedrock

     •     Amazon SageMaker

     •     AWS Lambda

     •     ECS/EKS

     •     AWS Data and Analytics services

     •     AWS Security and Governance services

AI & Data Technologies

     •     RAG architectures

     •     Vector databases (Pinecone, Weaviate, Milvus, Chroma, Azure AI Search)

     •     LangChain, LangGraph, LlamaIndex

     •     AI Agents and Agentic Workflows

     •     MLOps and LLMOps

     •     Model monitoring and evaluation frameworks

Programming

     •     Python

     •     SQL

     •     REST APIs

     •     Microservices Architecture

     •     CI/CD and DevOps practices

Preferred Qualifications

     •     Master's degree in Computer Science, Artificial Intelligence, Data Science, or related field.

     •     Experience with enterprise AI governance and Responsible AI frameworks.

     •     Experience in regulated industries such as healthcare, financial services, defense, or technology.

     •     Experience integrating AI solutions with ERP, CRM, and enterprise systems.

Preferred Certifications

     •     Microsoft Certified: Azure Solutions Architect Expert

     •     Microsoft Certified: Azure AI Engineer Associate

     •     AWS Certified Solutions Architect Professional

     •     AWS Certified Machine Learning Specialty

     •     Google Professional Cloud Architect

     •     Google Professional Machine Learning Engineer

Success Metrics

     •     Delivery of scalable enterprise AI solutions.

     •     Successful deployment of GenAI applications into production.

     •     Adoption of AI platforms and architecture standards across business units.

     •     Improved operational efficiency and business outcomes through AI-driven initiatives.

     •     Establishment of secure, governed, and responsible AI practices

Key Skills

Education

Any Graduate