AI Architect

Job Title:

AI Architect

Location:

Remote

• Define enterprise AI reference architectures that enable rapid experimentation, scalable deployment, and long-term maintainability
• Design end-to-end AI solutions spanning data ingestion, model development, deployment, and monitoring layers
• Ensure architectural decisions balance innovation with enterprise standards for security, performance, and cost optimization
• Create reusable patterns, templates, and accelerators that reduce time-to-value for AI implementations

• Architect data ecosystems that provide high-quality, accessible, and governed data for AI/ML workloads
• Design MLOps pipelines enabling continuous integration, delivery, and monitoring of AI models at scale
• Establish feature stores, model registries, and versioning frameworks that ensure reproducibility and traceability
• Optimize data architectures for real-time inference, batch processing, and hybrid deployment scenarios

• Define cloud-native AI platform strategies leveraging Azure, AWS, GCP, or hybrid environments
• Evaluate and recommend AI/ML platforms, tools, and frameworks aligned with client capabilities and objectives
• Design infrastructure architectures that optimize compute, storage, and networking for AI workloads
• Ensure platform choices support scalability, cost efficiency, and future technology evolution

• Embed governance, security, and compliance requirements into AI architecture from design phase
• Design model explainability, bias detection, and fairness monitoring capabilities into solution architectures
• Architect audit trails, lineage tracking, and access controls that meet regulatory requirements
• Ensure architectures support responsible AI principles including transparency, accountability, and privacy

• Translate business requirements into technical architectures that stakeholders across business and IT can understand
• Guide cross-functional teams including data engineers, data scientists, and Dev Ops through implementation
• Influence enterprise architecture decisions to ensure AI readiness across technology landscape
• Serve as technical authority on AI initiatives, resolving design conflicts and ensuring architectural integrity

• Evaluate emerging AI technologies (GenAI, LLMs, edge AI) and assess applicability to client contexts
• Define technology roadmaps that evolve AI capabilities in alignment with business strategy
• Lead proof‑of‑concepts and technical pilots to validate architectural approaches before scale
• Contribute to intellectual property through reusable assets, frameworks, and technical publications

• Enterprise AI Architecture:
  Proven ability to design scalable, production‑grade AI architectures that support diverse use cases from experimentation through enterprise‑wide deployment with measurable business impact
• Data Engineering & MLOps:
  Mastery, deep expertise in architecting data pipelines, feature stores, model registries, and MLOps frameworks enabling continuous delivery and monitoring of AI models at scale
• Cloud & Platform:
  Expertise, extensive hands‑on experience with cloud‑native AI services across Azure (Azure ML, Synapse, Databricks), AWS (Sage Maker, Bedrock), or GCP (Vertex AI) with ability to design hybrid and multi‑cloud solutions
• Technical Leadership:
  Strong ability to lead technical teams, resolve complex design challenges, and communicate architectural decisions effectively to both technical and business stakeholders
• Governance & Security:
  Integration experience embedding responsible AI principles, security controls, and regulatory compliance into AI architectures from design through deployment

• 10‑15 years of overall IT experience with minimum 8+ years focused on data engineering, AI/ML, and solution architecture
• 5+ years of experience designing and delivering enterprise‑scale AI/ML and GenAI solutions in production environments
• Demonstrated track record of leading architecture for AI transformation programs across multiple industries
• Experience working with Fortune 500 or large enterprise clients in consulting or technology delivery roles
• Knowledge of AI Governance and Responsible & Ethical AI practices
• MBA preferred