Forward Deployed AI Engineer - Associate Manager

Role overview

Responsibilities

• Lead enterprise AI platform deployments from architecture through adoption and iteration, owning quality, time-to-value, reliability, adoption, and scalability.
• Prototype and deploy AI-enabled workflows, agents, copilots, and automations into operational environments.
• Architect and govern AI solutions across identity, data, security, governance, platform layers, and multi-system integrations.
• Design prompts, workflows, API integrations, orchestration, enterprise knowledge integration, and privacy considerations; guide secure, responsible deployment.
• Develop client AI strategy, value architecture, ROI backlogs, use-case priorities, and multi-year adoption roadmaps.
• Codify delivery learnings and standards into reusable blueprints, patterns, and accelerators.
• Lead architecture sessions, executive workshops, and code-with sessions with client teams.
• Translate evolving client needs into technical solutions and connect product, engineering, data, and business stakeholders.
• Build end-to-end AI solutions integrating LLMs and AI services with enterprise platforms and internal systems.

Required qualifications

• Bachelor's degree or college diploma in a related field.
• At least 7 years of cloud-native engineering experience, including APIs, microservices, containerization, and serverless architectures.
• At least 5 years of software engineering using Java, TypeScript/JavaScript, or Python, and 5 years integrating APIs and building distributed production systems.
• At least 1 year designing and deploying production agentic solutions, including agents, orchestration, context engineering, RAG, or workflows.
• At least 1 year applying AI-native and agentic development practices across the software development lifecycle, including spec-driven development and AI coding agents.
• At least 1 year working with AI platforms such as OpenAI, Claude, Vertex AI, or open-source models, including multi-provider abstractions and enterprise AI platforms.
• At least 7 years leading and developing software engineering teams, including delivery oversight, resource allocation, performance management, and direct-report development.
• At least 5 years in client-facing communication and collaboration, including technical discussions, workshops, or delivery sessions under ambiguity.
• At least 5 years translating business needs into technical designs and implementations in large enterprises or a professional services firm.
• Demonstrated end-to-end ownership of client-embedded enterprise AI deployments across multi-stakeholder environments.
• Experience defining enterprise AI architecture across identity, data, security, governance, and multi-system integrations.
• Experience working with CTO-, CFO-, or CISO-level stakeholders on AI strategy and investment decisions.

Compensation

• The stated annual salary range for British Columbia, Ontario, and New Brunswick is CAD 100,300–216,700.
• The compensation range is stated for full-time employment and may vary by location, role, skills, and experience.

Travel

• Travel may be required, varying from 25% to 75% according to business need and client requirements.