Location: Toronto, Ontario, Canada - Hybrid (2 days onsite in a week)
Duration: 2 Years (extension possible at tenure; conversion possible)
Schedule: Monday–Friday, core business hours (overtime not likely)
Job Description:
- The Full Stack Solution Architect will work within the Infrastructure & Engineering (I&E) business as part of the broader Solution Architecture Practice.
- This independent-contributor role acts as the technical advisor to I&E - creating architectural target states, helping prioritize product roadmaps, and collaborating closely with platform technology teams to create solutions that meet business needs.
- The Architect will design end-to-end AI solution architectures, including AI/LLM gateways, agentic AI platforms, model access patterns, RAG and knowledge-retrieval patterns, AI observability, security guardrails, and governed integration with enterprise APIs, data platforms, and cloud infrastructure.
- The role leads project/product architecture blueprints and high- and low-level design specifications, ensuring solutions are scalable, reliable, secure, cost-aware, and compliant with enterprise architecture standards.
- The Architect will also develop and maintain architecture frameworks and solution patterns that support responsible, resilient, production-ready AI capabilities across hybrid and multi-cloud environments - covering identity and access management, model routing, token and cost governance, prompt and response controls, data protection, observability, and operational readiness.
Responsibilities:
- Align internal and external stakeholders on the architecture/infrastructure of the product strategy and delivery roadmap, engaging the Executive Product Owner.
- Lead architecture-backlog prioritization and advise on business/technology trade-offs.
- Oversee the portfolio of product-based delivery work.
- Review, approve/veto architecture blueprints against enterprise standards.
- Identify, recommend, source, negotiate and implement emerging IT trends and improvements (buy/build/reuse).
- Steer creation of consumable assets and reference architectures; get architecture tested and into production.
- Hold decision rights on architecture strategies, policies, roles and responsibilities within the assigned Platform/Journey.
- Oversee design of applications/infrastructure on high-profile, complex, high-risk technology projects.
- Drive end-to-end Kubernetes adoption and optimize container implementation.
- Lead AI architecture for enterprise GenAI/agentic AI: AI/LLM gateway patterns, agent orchestration, model access, RAG, MCP/tool integration, prompt management, safety controls, governed API/data integration.
- Define reusable AI reference architectures and decision frameworks balancing innovation, resiliency, security, privacy, cost transparency, model portability, and regulatory expectations.
- Set service-level objectives (SLOs) and develop observability standards for production systems.
- Lead interaction with governance and control groups (regulatory/operational risk, compliance, audit).
- Establish AI governance patterns: authentication & authorization, prompt-injection and jailbreak controls, sensitive-data protection, content safety, audit logging, model routing, token limits, quota management, monitoring.
- Partner with risk, cyber security, data governance, privacy, compliance, cloud and platform teams.
- Mentor and coach team members; contribute to building practice capability.
Experience:
- 10+ years of overall experience.
- Extensive hands-on architecture experience designing and delivering enterprise GenAI, LLM, and agentic AI solutions.
- Experience working in a regulated environment (banking or similar) is a nice-to-have.
Skillsets:
- CI/CD, pair programming and/or test-driven development (unit, integration and functional tests).
- Leading technical tools integration in a complex environment.
- AI agents, AI/LLM gateways, RAG, vector search, prompt orchestration, MCP/tool integration, model consumption patterns.
- AI platform architecture across cloud/hybrid: Azure OpenAI, Azure AI Foundry, Google Vertex AI/Gemini, model routing & lifecycle, AI observability, evaluation, responsible-AI guardrails.
- AI services: identity & access control, data protection, prompt/response safety, token & cost governance, semantic caching, fallback & resiliency, logging, tracing, auditability.
- Strong communication skills - able to engage stakeholders at all levels, including executives.
Education: Undergraduate degree required; graduate degree is a nice-to-have.
Additional Qualifications:
Licenses: None required.
Certifications: No certifications required - AI, cloud, architecture, security, or data certifications are preferred.
Shift Hours: Monday–Friday, core business hours.
About US Tech Solutions:
US Tech Solutions is a global staff augmentation firm providing a wide range of talent on-demand and total workforce solutions. To know more about US Tech Solutions, please visit www.ustechsolutions.com.
US Tech Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
AI Statement: By applying, you acknowledge that AI-assisted tools may be used during hiring.
