Is the AI Architect role on-site?

Yes — this role is on-site at the client's Totonto, ON location, five days per week. The client's culture and delivery cadence are calibrated around in-person collaboration for this position. Relocation support may be available for the right candidate; the recruiter will confirm during your calibration call.

Is this a contract or full-time role?

This is a contract opportunity on ApTask's payroll. If selected, you will be employed by ApTask and will receive a W-2 for the duration of your assignment. During your engagement, you will be eligible for subsidized benefits, including medical, dental, vision insurance, a 401(k) plan, commuter benefits, and state-mandated paid sick leave. Your pay cycle (weekly or biweekly, as applicable) will be confirmed at the time of your offer. You'll also have a dedicated ApTask recruiter as your single point of contact throughout your assignment, providing ongoing support from onboarding through completion. Many of our contract opportunities are extended or converted to permanent positions based on business needs and performance. Your recruiter can share the client's historical extension and conversion trends during the interview process. Benefits, assignment duration, extension, conversion opportunities, and eligibility are subject to client requirements, business needs, and applicable plan terms.

What is the compensation range for this role?

The advertised range for this AI Architect role is $70–$75 per hour. Where you land within the band depends on validated experience, the specific stack calibration match, and — for contract engagements — the bill-rate the client has locked in for this requisition. The recruiter will discuss the exact number during your calibration call.

How quickly does the interview process move?

If your profile is a fit for this role, you can expect the recruiter's first call within one business day. From there, interview cadence depends on the client's hiring-manager and panel availability. Total time from submission to signed offer varies by client — pre-verified profiles and calibrated submissions cut the noise, but the pace of interviews is driven by the client, not us.

What technical skills does the AI Architect role require?

The client is targeting depth in AI. Adjacent experience is welcome — we routinely place candidates whose exact stack match is 60-70% when the underlying pattern (distributed systems, regulated-data handling, or comparable) is strong. Bring the full stack breadth to your calibration call; the recruiter will map it onto the client's evaluation scorecard.

OnsitecontractorReq 26-02447Posted 17 days ago

AI Architect

Contract role in Totonto, ON. Onsite engagement, matched and submitted by an ApTask vertical recruiter.

Location: Totonto, ON · Onsite
Compensation: $70–$75/hr

Talk to a recruiter

Your résumé routes to the vertical recruiter who owns this requisition. Identity-verified profile, never resold or syndicated.

Stack

About the role

At a glance

AI summary

Day-to-day: Design enterprise-scale Generative AI solutions on GCP. Lead RAG, LLM, and Agentic AI architecture implementation. Conduct architecture reviews and mentor engineering teams on AI adoption
You'll bring: 10 years software engineering or cloud architecture experience. 5 years designing AI/ML solutions. 3 years delivering Generative AI in enterprise. Bachelor's in Computer Science or Data Science. Expertise in Vertex AI, RAG, LLMs, vector databases, Python, LangChain
Good fit if: You hold Google Cloud Professional Cloud Architect or Machine Learning Engineer certifications. You have Databricks Generative AI certifications. You've implemented GraphRAG or knowledge graph solutions at scale

Generated from the recruiter description below. The full posting is the source of truth — always read it before applying.

About Client:
The client provides information technology (IT) services, including business outsourcing, infrastructure technology, and application services. The application service offered by the company includes application development, maintenance, and support. The markets served by the company are financial services and insurance, healthcare, manufacturing, government, transportation, communications, and consumer and retail industries.

Rate: $70/Hr

Job Description:

We are seeking a highly experienced AI Architect to lead the design, architecture, and implementation of enterprise-scale Generative AI solutions on Google Cloud Platform (GCP).
The ideal candidate will possess deep expertise in Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), Agentic AI, Vector Databases, and the Google AI ecosystem including Vertex AI and Gemini.
The role requires a blend of strategic architecture leadership and hands-on technical expertise to deliver scalable, secure, and production-ready AI platforms.

Years of Experience:

10 years of overall experience in software engineering, cloud architecture, or data platforms.
5 years of experience designing and implementing AI/ML solutions.
3 years of experience delivering Generative AI and LLM-based applications in enterprise environments.
Proven experience implementing RAG architectures, conversational AI platforms, and AI-powered knowledge management solutions.

Technical Skills:
Required:

Bachelor s degree in Computer Science, Data Science.
Generative AI & LLMs: Gemini, Vertex AI, OpenAI, Llama, Foundation Models, Prompt Engineering, Conversational AI, Agentic AI / Multi-Agent Architectures, AI Model Evaluation and Monitoring
RAG & Knowledge Systems: Retrieval-Augmented Generation (RAG), GraphRAG, Knowledge Graphs, Semantic Search, Embeddings and Vector Search, Document Intelligence and Enterprise Search
Google Cloud Platform (GCP): Vertex AI, BigQuery, Cloud Storage, Cloud Run, Cloud Functions, Cloud SQL, Pub/Sub, Dataflow, GKE (Google Kubernetes Engine)
Vector Databases & Search: Vertex AI Vector Search, Pinecone, ChromaDB, FAISS, pgVector
AI Frameworks & Development: LangChain, LangGraph, LlamaIndex, FastAPI, REST APIs, Python, SQL
MLOps & DevOps: Vertex AI Pipelines, MLflow, CI/CD for AI Applications, Model Governance & Monitoring, Infrastructure as Code (Terraform)
Security & Governance: Responsible AI, AI Risk Management, Data Governance, Security Architecture, Compliance & Audit Controls

Preferred Certifications:

Google Cloud Professional Cloud Architect
Google Cloud Professional Machine Learning Engineer
Google Generative AI Certifications
Databricks Generative AI Certifications (preferred)

Key Responsibilities:
AI Architecture & Strategy:

Define enterprise AI architecture standards, patterns, and best practices.
Design end-to-end Generative AI, RAG, and Agentic AI solutions.
Develop AI roadmaps aligned with business objectives and technology strategy.

RAG & Knowledge Platform Design:

Architect large-scale RAG and GraphRAG solutions.
Design document ingestion, chunking, indexing, retrieval, re-ranking, and grounding strategies.
Optimize AI solution accuracy, scalability, latency, and cost efficiency.
Build enterprise knowledge platforms leveraging structured and unstructured data sources.

Generative AI Solution Delivery:

Lead the design and implementation of AI assistants, chatbots, copilots, and autonomous agents.
Enable integration of LLMs with enterprise systems, APIs, and workflows.
Establish frameworks for prompt engineering, model evaluation, and continuous improvement.

Cloud & Platform Engineering:

Architect scalable AI platforms using GCP services.
Drive cloud-native AI application development and deployment.
Define best practices for performance optimization, reliability, observability, and resilience.

Governance, Security & Responsible AI:

Implement AI governance frameworks, security controls, and monitoring capabilities.
Ensure compliance with enterprise policies, data privacy, and regulatory requirements.
Establish standards for model transparency, explainability, and risk management.

Leadership & Collaboration:

Partner with business stakeholders, product owners, data engineers, and AI teams.
Conduct architecture reviews and technical design workshops.
Mentor engineering teams and promote AI adoption across the organization.
Present architecture recommendations and investment strategies to executive leadership.

About ApTask:
ApTask is a leading global provider of workforce solutions and talent acquisition services, dedicated to shaping the future of work. As an African American-owned and Veteran-owned company, ApTask offers a comprehensive suite of services, including staffing and recruitment solutions, managed services, IT consulting, and project management. With a focus on excellence, collaboration, and innovation, ApTask provides unparalleled opportunities for professional growth and development. As a member of the ApTask team, you will have the chance to connect businesses with top-tier professionals, optimize workforce performance, and drive success across diverse industries. Join us at ApTask and be part of our mission to empower organizations to thrive while fostering a diverse and inclusive work environment.

Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview.

Candidate Data Collection Disclaimer:
At ApTask, we prioritize safeguarding your privacy. As part of our recruitment process, certain Personally Identifiable Information (PII) may be requested by our clients for verification and application purposes. Rest assured, we strictly adhere to confidentiality standards and comply with all relevant data protection laws. Please note that we only collect the necessary information as specified by each client and do not request sensitive details during the initial stages of recruitment.

If you have any concerns or queries about your personal information, please feel free to contact our compliance team at [email protected].

Applicant Consent:
By submitting your application, you agree to ApTask's (www.aptask.com) Terms of Use and Privacy Policy, and provide your consent to receive SMS and voice call communications regarding employment opportunities that match your resume and qualifications. You understand that your personal information will be used solely for recruitment purposes and that you can withdraw your consent at any time by contacting us at 732-355-8000 or [email protected]. Message frequency may vary. Msg & data rates may apply.

About technology at ApTask

What this vertical looks like inside ApTask.

Technology roles at ApTask cover the software, cloud, data, security, and platform-engineering functions that power Fortune 500 digital operations. Our recruiters specialise in high-signal technical calibration — every candidate is validated against the specific stack, framework versions, and deployment context the client runs, not a keyword match. Our largest engagements sit inside AWS, Azure, GCP, Snowflake, Databricks, and modern data-mesh estates. Because we route through Fieldglass, Beeline, Workday VNDLY, and Coupa VMS, technology contractors placed through ApTask carry MBE diversity spend against the client's supplier program while remaining W-2 with full benefits under our payroll.

How it works

What happens after you apply.

1. Verified profile
Submit your résumé and complete the ApTask identity + skills verification. We check right-to-work, background, and technical calibration once — never resell or re-verify — so future roles surface faster.
2. Recruiter calibration call
Within one business day, the recruiter who owns this requisition reviews your profile against the client's specific stack, arrangement, and start-date requirements. You'll hear back either way — no ghosting.
3. Client interview
If your profile is a fit, we present you to the hiring team. Most clients run 2-3 interview stages: hiring-manager screen, technical panel, and final. We prep you with the exact scorecard criteria before each round.
4. Offer + onboarding
On acceptance, you onboard W-2 with ApTask (contract) or direct-hire with the client (per role type). Benefits, payroll, and timesheets run through us. Your recruiter stays your point of contact for the length of the engagement.

Frequently asked

Questions candidates ask about this role.

Is the AI Architect role on-site?: Yes — this role is on-site at the client's Totonto, ON location, five days per week. The client's culture and delivery cadence are calibrated around in-person collaboration for this position. Relocation support may be available for the right candidate; the recruiter will confirm during your calibration call.
Is this a contract or full-time role?: This is a contract opportunity on ApTask's payroll. If selected, you will be employed by ApTask and will receive a W-2 for the duration of your assignment. During your engagement, you will be eligible for subsidized benefits, including medical, dental, vision insurance, a 401(k) plan, commuter benefits, and state-mandated paid sick leave. Your pay cycle (weekly or biweekly, as applicable) will be confirmed at the time of your offer. You'll also have a dedicated ApTask recruiter as your single point of contact throughout your assignment, providing ongoing support from onboarding through completion. Many of our contract opportunities are extended or converted to permanent positions based on business needs and performance. Your recruiter can share the client's historical extension and conversion trends during the interview process. Benefits, assignment duration, extension, conversion opportunities, and eligibility are subject to client requirements, business needs, and applicable plan terms.
What is the compensation range for this role?: The advertised range for this AI Architect role is $70–$75 per hour. Where you land within the band depends on validated experience, the specific stack calibration match, and — for contract engagements — the bill-rate the client has locked in for this requisition. The recruiter will discuss the exact number during your calibration call.
How quickly does the interview process move?: If your profile is a fit for this role, you can expect the recruiter's first call within one business day. From there, interview cadence depends on the client's hiring-manager and panel availability. Total time from submission to signed offer varies by client — pre-verified profiles and calibrated submissions cut the noise, but the pace of interviews is driven by the client, not us.

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