Forward Deployed AI Engineer - Associate Manager

Role overview

Key responsibilities

• Lead AI platform deployments from architecture through adoption and ongoing iteration, accountable for 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 spanning identity, data, security, governance, platform layers, and multi-system integration.
• Design prompts, workflows, API integrations, orchestration, enterprise knowledge integration, and privacy considerations.
• Develop AI strategy, value architecture, ROI backlogs, use case prioritization, and multi-year adoption roadmaps with senior client stakeholders.
• Create reusable reinvention blueprints, patterns, and accelerators from delivery learnings.
• Lead architecture sessions, executive workshops, and code-with sessions.
• Translate ambiguous business problems into technical solutions and connect product, engineering, data, and business stakeholders.
• Implement end-to-end AI solutions integrating LLMs and services such as OpenAI, Anthropic, and Gemini with enterprise platforms including SAP, ServiceNow, and Salesforce.

Basic qualifications

• Bachelor’s degree or college diploma in a related field.
• At least 7 years of cloud-native engineering, 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 lifecycle, including spec-driven development and AI coding agents.
• At least 1 year with AI platforms such as OpenAI, Claude, Vertex AI, or open-source models, including multi-provider pipeline abstraction.
• At least 7 years leading and developing software engineering teams, including delivery oversight, resource allocation, performance management, and staff development.
• At least 5 years in client-facing technical communication and collaboration, including workshops or delivery sessions under ambiguity.
• At least 5 years translating business needs into technical designs in large enterprises or professional services.
• Experience owning end-to-end client-embedded enterprise AI deployments, defining enterprise AI architecture, and advising senior stakeholders on AI strategy and investment.

Work arrangement and travel

• Work is embedded in client enterprise environments.
• Travel may be required, varying from 25% to 75% based on business needs and client requirements.

Compensation

• Annual base pay range for British Columbia, Ontario, and New Brunswick is CAD 100,300 to CAD 216,700; actual compensation depends on role, location, skills, and experience.