Devops jobs in Canada

The Senior Director, Head of Core GenAI Services Engineering, is a pivotal, senior technical leadership role reporting to the VP, R&D Technology Ecosystem. This role demands a unique combination of deep, hands‑on architectural expertise, strategic vision, and people leadership, grounded in a proven ability to lead distributed engineering teams across diverse, complex technical landscapes.

You will drive the strategy, design, and operational execution for the organization's core internal GenAI capabilities, specifically owning the Core GenAI Services and the GenAI Gateway — a centralized API service that provides secure, standardized, and scalable access to GenAI models (LLMs, SLMs) and orchestration frameworks for internal teams across the R&D landscape.

Success in this position requires a leader with a proven track record of AI transformation, upskilling, and mentoring, capable of translating complex business needs in the pharmaceutical space into technical decisions that unlock massive scale and adoption. You will shape and continuously refine the internal engineering culture, championing principles of extreme ownership (“you build it, you own it”) and accelerating delivery through rapid feedback loops.

Driving GenAI Strategy: Define and own the long‑term vision and technical strategy for internal Core GenAI capabilities, ensuring alignment with enterprise AI goals and R&D business priorities.

AI Transformation & Upskilling: Lead the organizational AI transformation efforts, including upskilling and capability development across engineering and R&D teams.

Advanced Communication & Stakeholder Alignment: Leverage strong communication skills and experience interacting with senior customer and business stakeholders to drive consensus and adoption.

Standards & Best Practices: Drive standards, playbooks, and global best practices for LLMs, SLMs, retrieval‑augmented generation (RAG), orchestration frameworks, and GenAI architectures, specifically tailored for the highly regulated pharmaceutical space.

Core GenAI Ownership: Own the architecture and development of the Core GenAI Services and the high‑performance, centralized GenAI Gateway, ensuring resilience, security, and low‑latency API access for all consuming teams.

Deep GenAI Expertise: Provide hands‑on architectural depth based on a deep understanding of GenAI technologies (LLMs, SLMs, RAG, AI agents, orchestration frameworks) and modern software/cloud architectures.

AI Productionization: Apply expertise in productionizing complex AI‑based systems, leveraging experience from diverse domains including Computer Vision and Security applications, including robust evaluation, deployment, monitoring, and governance frameworks (MLOps).

Architectural Evolution: Own and evolve the platform architecture and technical strategy, ensuring scalability, reliability, security, and cost efficiency across the cloud footprint.

Team Building: Build and lead a high‑performing technical team of software engineers, machine learning engineers, and devops/infrastructure engineers.

Mentorship & Development: Actively mentor and develop our internal engineering talent pool, providing technical coaching that deepens expertise in AI / ML systems and platform engineering.

Cultural Definition: Define and evolve the internal engineering culture, championing extreme ownership, high quality, data‑driven decision‑making, and short, iterative feedback cycles.

Talent Growth: Lead, mentor, and grow teams of individual contributors and team leads, fostering a culture of technical excellence, continuous learning, and structured career development.

Oversee the development of reusable SDKs, APIs, CLI tools, and developer platforms to maximize the adoption of GenAI capabilities.

Drive creation of reusable components, frameworks, and infrastructure that accelerate the full GenAI model lifecycle workflows.

Champion developer experience and platform adoption through high‑quality documentation, enablement, and direct feedback loops with consuming teams.

This role requires the unique breadth and depth of a highly seasoned leader who can operate effectively at the executive level while maintaining deep technical credibility with engineers.

Senior Engineering Leader (15+ years experience, 10+ years leadership) driving innovation in AI, Machine Learning, Computer Vision, and Security. Proven success in building and scaling distributed engineering & research teams across diverse technical landscapes (incl. AR / VR, GIS, Cybersecurity) from startup to large‑enterprise scale. Deep experience in applying AI to real‑world problems, currently focusing on behavior understanding for security applications. This background provides a critical perspective for developing secure, high‑performance, and compliant GenAI services.

15+ years of hands‑on software engineering experience with deep expertise in system architecture, platform development, and production AI / ML systems.

10+ years of progressive leadership and people management experience (including managing managers or sub‑teams).

Demonstrated expertise in productionizing AI‑based systems and scaling them for enterprise use across multiple, high‑stakes domains (e.g., Computer Vision, Cybersecurity, GIS).

Expert‑level production Python and extensive cloud (AWS) architecture experience designing complex, scalable GenAI systems.

Deep understanding of GenAI technologies (LLMs, SLMs, RAG, orchestration frameworks) and modern software/cloud architectures.

Proven stakeholder management, executive communication, and cross‑functional delivery in complex, regulated environments.

Bachelor’s or Master’s degree in Computer Science, Engineering, AI / ML, or related technical field.

Experience defining GenAI standards, playbooks, and best practices in the pharmaceutical, healthcare, or other highly regulated industries.

Track record of building and leading world‑class, multi‑disciplinary technical teams (SWEs, MLEs, DevOps).

Demonstrated expertise in fields directly applicable to R&D, such as Computer Vision, Geospatial Information Systems (GIS), or robust AI systems in a high‑security context.

Experience with advanced LLM frameworks and services (e.g., Anthropic Claude, Azure OpenAI, Amazon Bedrock) and orchestration tools (LangChain, LlamaIndex).

Advanced knowledge of AWS services, microservices, event‑driven architectures, and distributed systems.

PhD in Computer Science, AI / ML, or related field.

Breakthroughs that change patients' lives … At Pfizer we are a patient‑centric company, guided by our four values: courage, joy, equity and excellence. Our breakthrough culture lends itself to our dedication to transforming millions of lives.

One bold way we are achieving our purpose is through our company‑wide digital transformation strategy. We are leading the way in adopting new data, modeling and automated solutions to further digitize and accelerate drug discovery and development with the aim of enhancing health outcomes and the patient experience.

We aim to create a trusting, flexible workplace culture which encourages employees to achieve work‑life harmony, attracts talent and enables everyone to be their best working self. Let’s start the conversation!

We believe that a diverse and inclusive workforce is crucial to building a successful business. As an employer, Pfizer is committed to celebrating this in all its forms – allowing for us to be as diverse as the patients and communities we serve. Together, we continue to build a culture that encourages, supports and empowers our employees.

Our mission is unleashing the power of all our people and we are proud to be a disability inclusive employer, ensuring equal employment opportunities for all candidates. We encourage you to put your best self forward with the knowledge and trust that we will make any reasonable adjustments to support your application and future career. Your journey with Pfizer starts here!