AI Solutions Architect | US

Stack

Responsibilities

• ▹Design cloud-native AI and data solution architectures (reference patterns, data flows, AI/ML workflows, LLM orchestration)
• ▹Translate AI and data architectures into diagrams, executive-ready narratives, and roadmaps
• ▹Advise clients on AI strategy, build-vs-buy decisions, governance, and ethical considerations
• ▹Integrate and orchestrate data across multiple platforms (e.g. Snowflake, BigQuery, Databricks, external APIs)
• ▹Collaborate with ML Engineers and Data Engineers to validate architectural alignment and feasibility
• ▹Conduct architecture reviews and risk assessments; execute course corrections as needed
• ▹Architect AI solutions using LLMs and RAG patterns for interpretable, human-readable outputs
• ▹Mentor junior architects and consultants; contribute to reusable accelerators and internal knowledge base
• ▹Provide technical oversight across multiple client engagements, ensuring consistency and quality
• ▹Provide hands-on guidance to engineering/data teams on API integrations, data pipelines, AI service connectivity
• ▹Stay current on emerging AI platforms, LLM tooling, and cloud-based data services

Requirements

• ▹8+ years in solution architecture, data engineering, or software engineering roles; 3+ years architecting AI/ML solutions in production
• ▹Proven experience designing cloud-native AI solutions and integrations across AWS, Azure, or GCP, including data platform integration, LLM orchestration, and secure API connectivity
• ▹Hands-on experience with at least two of: deep-learning frameworks (TensorFlow, PyTorch, JAX), NLP/LLM stacks (Hugging Face, LangChain, vector databases, RAG patterns), computer-vision pipelines (OpenCV, TorchVision), AutoML & orchestration (Vertex AI, SageMaker, MLflow, Kubeflow, Airflow)
• ▹Solid grounding in data modeling, API design (REST/GraphQL), containerization (Docker, Kubernetes), and IaC (Terraform, CloudFormation, or Pulumi)
• ▹Exceptional communication skills across engineering and executive levels
• ▹Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience)
• ▹Consulting or professional-services experience

Nice to have

• ▹Familiarity with privacy regulations (GDPR/CCPA) and AI governance frameworks (NIST AI RMF, ISO/IEC 42001 draft)
• ▹Track record leading GenAI POCs or production deployments (chatbots, copilots, content generation, autonomous agents)
• ▹Relevant certifications (AWS Solutions Architect Professional, Google Professional Cloud Architect, Microsoft Azure Solutions Architect, TensorFlow Developer)

Soft skills