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Staff AI Developer

  • Canada
  • Remote
  • Posted Oct 29, 2026
  • 1 position

$170,000–$234,000 / year

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Employment type
Full-time
Experience level
Lead · 10+ years
Posting language
English
Working hours
40 hours per week

Job summary

Lead the end-to-end architecture, development, and deployment of production-grade AI and machine learning systems. Collaborate with cross-functional teams to define AI strategy while mentoring engineers and establishing high engineering standards.

Job details

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Staff AI Developer based in Canada. We are seeking a highly experienced Staff AI Developer to lead the architecture, development, and deployment of production-grade AI and machine learning systems. In this senior technical leadership role, you will drive complex AI initiatives from initial research and design through scalable production implementation. You will build advanced generative AI and agentic systems, strengthen ML infrastructure, and establish engineering standards that prioritize reliability, security, and responsible AI practices. Working closely with product, engineering, and business leaders, you will translate complex technical challenges into solutions that deliver measurable value. You will also mentor engineers, guide architectural decisions, and champion AI-forward development practices using tools such as Claude Code and Cursor. This opportunity is ideal for a hands-on technical leader who thrives in a fast-paced environment where production-ready AI solutions are delivered in short development cycles. \n Accountabilities Lead the end-to-end architecture, design, development, and deployment of complex AI and machine learning systems, taking ownership from research and prototyping through production at scale. Design, build, and continuously improve scalable ML platforms, pipelines, and infrastructure that enable reliable, repeatable model development and deployment across teams. Architect and deliver advanced generative AI applications and agentic systems that integrate effectively into enterprise workflows and solve complex business challenges. Establish AI architecture principles, engineering standards, and development practices that promote maintainability, scalability, reliability, security, and responsible AI implementation. Develop and optimize retrieval-augmented generation (RAG) pipelines, including chunking strategies, embedding models, vector databases, and advanced retrieval techniques. Implement evaluation frameworks and observability solutions for LLM-powered applications, creating new capabilities where existing tools and processes are insufficient. Apply AI safety principles and defensive techniques to address prompt injection, personally identifiable information (PII) handling, and other risks associated with production AI systems. Optimize AI system performance and operating costs through token economics, caching strategies, model routing, quantization, and other efficiency improvements. Design and integrate APIs connecting internal platforms, third-party services, and AI capabilities at scale. Leverage cloud technologies, particularly AWS services and generative AI offerings, to deliver secure, scalable, and production-ready solutions. Champion AI-forward engineering practices by using tools such as Claude Code and Cursor effectively and helping other engineers adopt them productively. Collaborate with product managers, engineers, and leadership to define AI strategy, align technical decisions with business objectives, and communicate architectural tradeoffs, risks, and opportunities. Lead technical design reviews and architecture discussions, encouraging rigorous evaluation, constructive feedback, and high engineering standards. Mentor junior and mid-level engineers through coaching, code reviews, pairing, and guidance on complex technical challenges. Take ownership of ambiguous, high-impact initiatives, balancing delivery speed with reliability, safety, scalability, and cost effectiveness. Requirements At least seven years of professional software development experience, including four or more years focused on production AI/ML systems and substantial hands-on experience with generative AI development. Strong software engineering expertise in Python or a comparable programming language, with a proven ability to design scalable, maintainable, and robust systems. Deep knowledge of cloud platforms, particularly AWS services and AWS generative AI offerings. Demonstrated experience designing, building, and deploying complex agentic systems in production environments. Advanced proficiency with AI frameworks, orchestration tools, and technologies used to build and operate generative AI applications. Strong experience with LLM evaluation frameworks and observability tools, including designing and implementing evaluation capabilities when existing solutions do not meet requirements. Comprehensive understanding of AI safety and responsible AI principles, including prompt injection defenses, privacy protection, and secure handling of personally identifiable information. Extensive hands-on experience building RAG pipelines, including document chunking, embedding models, vector databases, and advanced retrieval strategies. Strong API design and integration skills, with experience connecting internal systems and third-party services in scalable production environments. Advanced expertise in AI cost and performance optimization, including token usage management, caching, model routing, and quantization techniques. Working knowledge of Docker and Kubernetes for containerized application development, deployment, and operations. Demonstrated, day-to-day proficiency with AI-assisted coding tools such as Claude Code and Cursor, including the ability to use them effectively in professional software engineering workflows. Strong architectural judgment and the ability to evaluate technical tradeoffs, anticipate long-term implications, and make sound decisions in complex or ambiguous situations. Excellent communication skills, with the ability to explain AI concepts, technical risks, and architectural decisions to both technical and non-technical stakeholders. Proven technical leadership and mentoring capabilities, with a commitment to raising engineering standards and helping teams deliver high-quality AI systems. Benefits Competitive salary: Annual compensation ranging from CAD $170,000 to CAD $234,000. Remote work: Opportunity to work remotely from Canada. Technical leadership: Take ownership of high-impact AI architecture and production engineering initiatives. Cutting-edge AI development: Work with generative AI, agentic systems, RAG pipelines, LLM evaluation, and advanced orchestration technologies. Modern engineering tools: Use AI-forward coding tools such as Claude Code and Cursor as part of everyday development. Meaningful business impact: Build production-ready AI solutions designed to integrate into real-world enterprise workflows and deliver measurable results. Professional growth: Influence engineering standards, shape AI strategy, and contribute to the evolution of scalable AI infrastructure. Mentorship and collaboration: Help develop engineering talent while partnering with product, engineering, and business leadership. International exposure: The role includes approximately 20% US-based travel, with willingness to travel and attend an onsite final interview and onboarding required. \n How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1

What you’ll do

Lead the end-to-end architecture, development, and deployment of production-grade AI and machine learning systems. Collaborate with cross-functional teams to define AI strategy while mentoring engineers and establishing high engineering standards.

Requirements

Requires at least seven years of professional software development experience, with four or more years specifically in production AI/ML systems. Candidates must possess deep expertise in Python, AWS, generative AI frameworks, and RAG pipeline development.

Benefits

  • Competitive salary
  • Remote work
  • Technical leadership
  • Cutting-edge AI development
  • Modern engineering tools
  • Meaningful business impact
  • Professional growth
  • Mentorship and collaboration

Listed skills

  • Kubernetes · Preferred
  • Docker · Preferred
  • Machine learning · Preferred
  • Amazon Web Services · Preferred
  • Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

  • Artificial Intelligence
  • Machine Learning
  • Generative AI
  • Python
  • AWS
  • RAG pipelines
  • Agentic systems
  • LLM evaluation
  • System architecture
  • Cloud computing
  • Docker
  • Kubernetes
  • API design
  • Technical leadership
  • Mentoring
  • AI safety
  • Mentorship
  • Communication
  • Management
  • Operations
  • Reliability
  • Workflow Management
  • Influencing Skills
  • Leadership
  • Data Privacy
  • Amazon Web Services
  • Generative Artificial Intelligence
  • Artificial Intelligence Infrastructure
  • Responsible AI
  • General Data Protection Regulation (GDPR)
  • Economics
  • Coaching
  • Information Privacy
  • Research
  • Application Programming Interface (API)
  • Python (Programming Language)
  • Software Engineering
  • Business Objectives
  • Business Continuity Planning
  • Balancing (Ledger/Billing)
  • Technical Leadership
  • Observability
  • Scalability
  • Architectural Design
  • Maintainability
  • Docker (Software)
  • Code Review
  • Software Development
  • Prototyping
  • Vector Database

Job areas

  • Technology
  • Software
  • Data & Analytics
  • Engineering
  • Management & Leadership
  • AI Developer
  • Software Developer / Engineer
  • Software Developers

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