AI Solutions Architect | US
Cuesta Partners6 months ago
Remote, United StatesSenior
Base Salary
$145k - $188k/yr
Responsibilities
- Design cloud-native AI and data solution architectures, including reference patterns, data flows, AI/ML workflows, and LLM orchestration.
- Own solution design from customer discovery through handoff while balancing scalability, security, cost, speed to value, and business impact.
- Translate technical architectures into diagrams, narratives, visuals, roadmaps, and briefings for technical and executive stakeholders.
- Advise clients on AI strategy, build-versus-buy decisions, governance, privacy, and ethical considerations.
- Integrate and orchestrate data across cloud warehouses, data lakes, external APIs, and AI services.
- Collaborate with ML Engineers, Data Engineers, engineering teams, and product leadership to validate feasibility and architectural alignment.
- Conduct architecture reviews and risk assessments, and execute course corrections when needed.
- Architect LLM and RAG solutions that produce interpretable insights and human-readable outputs.
- Provide technical oversight across multiple client engagements and ensure delivery quality and architectural consistency.
- Mentor junior architects and consultants and contribute reusable accelerators, templates, and internal knowledge resources.
- Evaluate emerging AI platforms, LLM tooling, and cloud-based data services for integration opportunities.
Requirements
- 8+ years of experience in solution architecture, data engineering, or software engineering, including 3+ years architecting AI/ML solutions in production.
- Experience designing modern cloud-native AI solutions and integrations across AWS, Azure, or GCP, including data platforms, LLM orchestration, and secure API connectivity.
- Hands-on experience with at least two relevant technology areas, including deep-learning frameworks, NLP/LLM stacks, computer-vision pipelines, or AutoML and orchestration tools.
- Grounding in data modeling, REST or GraphQL API design, Docker, Kubernetes, and infrastructure-as-code tools such as Terraform, CloudFormation, or Pulumi.
- Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
- Consulting or professional-services experience.
- Strong communication skills for collaborating with engineers and briefing executive stakeholders.
- Preferred qualifications include privacy and AI governance knowledge, experience leading GenAI proofs of concept or production deployments, and relevant cloud or TensorFlow certifications.
Tech Stack
Apache AirflowAWSAzureDatabricksDockerGoogle BigQueryGoogle Cloud PlatformGraphQLKubernetesMLflowOpenCVPyTorchSnowflakeTensorFlowTerraform
Categories
Solutions Engineering