Solution Architect

Role

The role is that of a Solution Architect. In summary, that role is responsible for proposing technical, AI-based solutions for problems or opportunities already identified across PDT.

Responsibilities

• Analyzes an existing description of the problem or need where AI-based development can help, as for example from what is in a Product Requirements Document (PRD), and as needed, gathers additional understanding and extends the PRD, working in collaboration with the Product Manager.
• Creates a proposal of a high-level technical architecture (typically mainly software architecture, but there could still be other pieces, like manual steps) to best solve a problem previously defined, consisting of at least some AI components and any other needed components (front end, back end, infrastructure, data pipelines, new or refined neural network models, data, etc.).
• Works in collaboration with the Product Manager, a Project Manager, and technical implementation teams.

Qualifications

• A minimum of a Bachelors degree
• 5 years designing and delivering production software systems; proven ability to define service boundaries, APIs, and scalable architectures.
• 2 years developing or using ML, AI, or data driven solutions.
• Working knowledge of AI/ML system design, including data pipelines, deployment patterns, and operational monitoring.
• Strong data architecture fundamentals (batch/streaming, modeling, governance) and ability to derive data requirements from product needs.
• Experience with cloud infrastructure and deployment patterns; ability to design secure, observable systems.
• Excellent technical documentation skills: architecture diagrams, tradeoff analysis, and decision records.

Preferred Qualifications

• Experience architecting and delivering production LLM applications (RAG, vector search, tool calling/agents), including evaluation and guardrails.
• Hands-on MLOps/platform experience (CI/CD for ML, model registry, feature store, monitoring & drift detection).
• Experience in enterprise-scale, regulated environments and/or implementing responsible AI controls and auditability.
• Strong cost modeling skills for AI workloads (GPU serving, token cost optimization, capacity planning).
• A degree in an engineering field (e.g. computer, software, machine learning, intelligent systems, control systems, mechatronics, systems, mechanical engineering…) or a science field (e.g. physics, mathematics, …)
• Ability to work across teams.
• Ability to build agreement.
• Experience working with global teams.

Benefits

• Comprehensive Health & Well-being Coverage
• Family Building Benefit
• Generous Paid Time Off
• Competitive Retirement Savings Plans
• Income Protection & Insurance Options
• Company Vehicle Lease Program
• Tuition reimbursement
• Student loan refinancing programs
• 18 paid volunteer hours each year to make a difference in your community