Senior AI/ML Solutions Architect

Presales & Customer Engagement (30%)

• Act as the lead AI/ML architect in customer discovery, technical workshops, and solution presentations.
• Partner with sales and business development teams to craft single or multi-cloud AI/ML proposals, SOWs, and architectural visions.
• Translate business problems into actionable solution designs spanning AWS (eventually Azure and/or GCP).
• Communicate the value of cloud-native AI/ML and Generative AI capabilities to both technical and executive stakeholders.
• Support competitive bids, RFP/RFI responses, and AWS partner programs with high-quality technical input.
  
  

Architecture & Solution Delivery (50%)

• Design robust, scalable AI/ML and GenAI architectures using cloud-native services such as Amazon SageMaker, AWS Bedrock, AWS Lambda, Amazon Kinesis, Amazon Athena. Similar services from Azure and/or Google are plus.
• Lead the development of ML pipelines, model training, deployment, and MLOps workflows.
• Guide implementation teams to ensure architectural quality, security, and adherence to Well-Architected frameworks across clouds.
• Develop reusable templates, accelerators, and reference architectures for multi-cloud delivery.
• Conduct architecture reviews and ensure proper AI governance, observability, and compliance.
  
  

Practice Development & Leadership (20%)

• Mentor data engineers, machine learning engineers, and cloud architects across the organization.
• Help shape the AI/ML practice by defining standards, delivery models, and tooling strategy.
• Assist in hiring and onboarding future team members as the practice grows.
• Represent the company at cloud partner events, industry conferences, and thought-leadership activities.

Required

• 5+ years of experience in machine learning, AI solution architecture, or data science.
• 2+ years hands-on experience designing and deploying AI/ML solutions on AWS, working knowledge of Azure and GCP is a plus.
• Strong experience with at least one major cloud AI/ML platforms; familiarity with the other two is a plus.
• Deep understanding of MLOps practices, ML lifecycle management, and automation.
• Expertise with Python and common ML frameworks (TensorFlow, PyTorch, scikit-learn).
• Proven presales experience, including designing solutions, presenting to customers, and contributing to proposals.
• Ability to translate business requirements into cloud-native AI/ML designs.
• Exceptional communication and stakeholder management skills.
  
  

Preferred

• AWS Machine Learning – Specialty, or ability to achieve it within 6 months of start.
• Experience with LLMs, RAG architectures, embeddings, fine-tuning, vector stores, and GenAI platforms.
• Knowledge of Databricks, Snowflake, Hugging Face, or other advanced ML ecosystems.
• Experience leading technical teams or contributing to practice development.
• Consulting background supporting enterprise clients across multiple industries.