Job Description
We are seeking an exceptional AI Software Architect to lead technical strategy and architecture design for 8-week AI solution assessments serving traditional businesses undergoing digital transformation. This role operates at the forefront of AI consulting, working directly with C-level executives, IT leaders, and enterprise architects to evaluate AI readiness, design comprehensive AI strategies, and deliver actionable technical roadmaps that drive business value and competitive advantage.
Responsibilities
AI Strategy & Architecture Leadership
Lead the technical strategy development for 8-week AI solution assessments, working with clients ranging from $20M to $500M+ annual revenue
Design comprehensive AI architectures incorporating Microsoft Azure AI Services, AWS AI/ML, and Google Cloud AI platforms
Evaluate and recommend AI technology stacks, frameworks, and deployment models tailored to client business objectives and technical constraints
Develop multi-cloud and hybrid-cloud infrastructure patterns optimized for AI workloads and enterprise integration requirements
Client Engagement & Technical Assessment
Conduct in-depth technical assessments of client data landscapes, existing infrastructure, and technology readiness for AI implementation
Lead stakeholder interviews with CTOs, IT Directors, Enterprise Architects, and technical teams to understand current state and future vision
Perform comprehensive evaluations of data quality, availability, governance frameworks, and integration capabilities
Assess MLOps maturity, model deployment capabilities, and scalability requirements for enterprise AI solutions
Solution Design & Proof of Concept Development
Architect and oversee development of working proof-of-concepts (PoCs) that demonstrate AI solution viability and business impact
Design API architectures and microservices patterns for AI model deployment and integration with existing enterprise systems
Implement machine learning models and convert them into production-ready APIs using modern containerization and orchestration technologies
Ensure PoCs demonstrate scalability, security, and performance characteristics required for enterprise deployment
Risk Management & Governance
Collaborate with security professionals and compliance teams to identify and mitigate AI-related risks including data privacy, model bias, and regulatory compliance
Develop AI governance frameworks and ethical AI principles tailored to client industry requirements (financial services, healthcare, manufacturing, retail)
Design monitoring and observability systems for AI model performance, drift detection, and explainability requirements
Create comprehensive risk assessment reports with mitigation strategies and implementation timelines
Deliverable Creation & Client Communication
Author detailed technical architecture documents, implementation guides, and technology roadmaps for executive and technical audiences
Present complex technical concepts and recommendations to C-level executives, translating technical constraints into business implications
Develop comprehensive AI maturity scorecards and improvement roadmaps with prioritized implementation phases
Create technical specifications for AI infrastructure, data pipelines, and integration patterns
Requirements
Education & Experience
Bachelor's or Master's degree in Computer Science, Engineering, or equivalent technical field
7+ years of experience in software architecture and enterprise system design
3+ years of specialized experience in AI/ML system architecture and implementation
2+ years of consulting experience or client-facing technical leadership roles
Technical Expertise
Expert-level proficiency in Python, Java, or R with deep understanding of AI/ML frameworks (TensorFlow, PyTorch, Scikit-Learn)
Extensive experience with cloud AI platforms (Azure AI Services, AWS AI/ML, Google Cloud AI) and their enterprise integration patterns
Strong expertise in containerization and orchestration technologies (Docker, Kubernetes) for AI workload deployment
Deep knowledge of data architecture, data governance, and MLOps frameworks for enterprise-scale AI implementations
AI & Domain Knowledge
Comprehensive understanding of machine learning model lifecycle, from development to production deployment and monitoring
Experience with vector databases (Pinecone, Milvus, Weaviate) and retrieval-augmented generation (RAG) architectures
Knowledge of AI model explainability, bias detection, and responsible AI practices for regulated industries
Understanding of enterprise data integration patterns, API design, and microservices architectures
Consulting & Communication Skills
Proven ability to lead technical assessments and deliver actionable recommendations to executive leadership
Strong presentation and communication skills with experience translating complex technical concepts for business stakeholders
Experience managing client relationships and delivering consulting engagements within defined timelines and budgets
Ability to work independently while collaborating effectively with cross-functional teams including product owners, data scientists, and business analysts
Preferred Skills
Preferred Qualifications
Advanced degree in Computer Science, AI/ML, or related technical field
Professional certifications in cloud platforms (Azure Solutions Architect, AWS Solutions Architect, Google Cloud Professional)
Experience with specific industry verticals (financial services, healthcare, manufacturing, retail) and their AI compliance requirements
Knowledge of enterprise architecture frameworks (TOGAF, Zachman) and their application to AI system design
Experience with agile consulting methodologies and project management frameworks
Previous experience with 8-week assessment engagements or similar time-boxed consulting deliverables
Success Metrics & Impact
Client Satisfaction & Engagement Success
Achieve 90%+ client satisfaction scores on technical assessment quality and deliverable value
Deliver 100% of 8-week assessments within scope, timeline, and budget constraints
Generate 70%+ follow-on engagement rate through high-quality technical recommendations and roadmaps
Technical Excellence & Innovation
Design AI architectures that achieve projected ROI within 18-24 months of implementation
Develop reusable technical frameworks and assessment methodologies that improve team efficiency
Stay current with emerging AI technologies and integrate innovative solutions into client recommendations
Tools & Technologies
AI/ML Platforms & Frameworks
TensorFlow, PyTorch, Scikit-Learn, Hugging Face
Azure AI Services, AWS AI/ML, Google Cloud AI
MLflow, Weights & Biases, Kubeflow
Vector databases: Pinecone, Milvus, Weaviate, Chroma
Cloud & Infrastructure
Microsoft Azure, Amazon Web Services, Google Cloud Platform
Docker, Kubernetes, Terraform
Git, GitHub, GitLab, Azure DevOps
Development & Integration
Python, Java, R, SQL
REST APIs, GraphQL, gRPC
Apache Kafka, Apache Airflow
Microservices architecture patterns
Consulting & Collaboration
Microsoft Office Suite, Google Workspace
Jira, Asana, Azure DevOps
Slack, Microsoft Teams, Zoom
Confluence, Notion, SharePoint
Category
Salary
Posted
Location
( Remote )
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