Principal Software Engineer / Principal AI Engineer

Overview

As Principal AI Engineer you lead the embedded Innovation Squad, driving AI architecture and delivery from discovery to production. You will harden prototypes, design reusable agentic AI patterns, and guide integration with enterprise systems. You serve as the senior AI technical authority, mentoring engineers and shaping scalable, secure AI solutions. This role combines hands-on design with stakeholder collaboration to deliver measurable impact across segments.

Pay / Benefits

• Comprehensive Pension Plan
• Generous vacation entitlement
• Maternity, Paternity, Adoption, and Family Care leave
• Personal Choice budget
• Employee Assistance Program (global)
• sabbatical leave option

Responsibilities

• Own technical execution from discovery to production; build, assess, and harden prototypes and proofs of concept, and deliver new ones.
• Design and govern reusable agentic AI patterns (orchestration, tool use, memory, retrieval).
• Ensure delivery meets architecture, security and data-governance standards; recommend infrastructure, hosting and data residency.
• Codify validated solutions into patterns, reference implementations, and starter kits for reuse across functions.
• Provide design input, finalize requirements, and work directly with internal stakeholders and end users in the host function.
• Write specifications, fix complex bugs, and design complex data models.
• Act as the primary technical contact for external resources and squad’s go-to on coding and AI.
• Establish baselines and report measurable outcomes for every initiative.
• Maintain visibility of in-flight AI pilots within the function to prevent duplication and surface candidates for reuse.
• Ensure alignment with enterprise non-negotiables: security, compliance and central technology infrastructure standards.
• Continuously evaluate emerging technologies and mentor and elevate team members.
• Take on related responsibilities as the squad’s needs evolve.

Key requirements

• Engineering experience: 10+ years in software engineering with hands-on AI system design, build or integration, and production-grade AI in enterprise environments.
• Education: BS in Engineering, Computer Science or equivalent; advanced degree preferred.
• Agentic AI / LLMs: orchestration, prompt engineering, context-window management and production guardrails; MCP, tool-augmented agents and RAG at enterprise scale.
• Enterprise integration: Integrating AI into enterprise systems via APIs and data pipelines with strong security, data governance and residency practices.
• Cloud: AWS, Azure or GCP, including managed AI/ML services.
• Delivery: Agile, CI/CD, modern SDLC and TDD.
• Data and architecture: Modelling across relational, columnar and vector stores, grounded in solid architectural principles.
• Ways of working: Thrives in ambiguity, framing the problem, extracting defined spec, and prioritises shipping validated outcomes over perfect solutions.
• Languages: Python, Java, TypeScript/JavaScript, SQL and relevant AI SDKs.
• Leadership and delivery management: Plans and sequences work, manages scope, dependencies and priorities, removes blockers, and drives delivery.
• Communication and influence: Presents concisely to senior management, stakeholders and cross-functional teams, and builds buy-in and drives technical decisions.
• Commercial awareness: Budget-aware; partners with internal and external resources, including managed services.
• Measurement: Establishes baselines and instruments solutions to track productivity, cost and quality outcomes from pilot through scale.

• Leadership and delivery management
• Communication and influence
• Commercial awareness
• LLM orchestration
• Prompt engineering
• Context-window management

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