Technical Program Manager, AI Delivery for Public Sector & Defence, Canada
About this role
Organized professionals who thrive at the intersection of government policy and advanced technology will find a natural home in this position at Cohere. Operating out of the Ottawa office, the selected candidate joins a customer-facing program management division dedicated entirely to Canadian public sector and defence accounts. Daily responsibilities center on guiding complex AI deployments through government procurement cycles, rigorous security frameworks, and strict data sovereignty requirements.
The team builds enterprise foundation models and comprehensive AI solutions, requiring the program lead to act as a crucial link between internal engineering groups and external government stakeholders. Success in the job demands a firm grasp of both modern machine learning architectures and bureaucratic processes, ensuring high-stakes projects move smoothly from initial deployment to production scaling while meeting all regulatory standards.
What you will do
- Own end-to-end technical program delivery for Canadian public sector and defence customers from initial deployment through production scaling.
- Serve as the primary technical program point of contact for government customers and build relationships with departmental IT leadership.
- Translate complex government requirements regarding security, compliance, accessibility, bilingualism, and data sovereignty into actionable engineering plans.
- Manage project schedules that account for government timelines, security review processes, and ministerial approval cycles.
- Coordinate technical work across multiple teams including model customization, security hardening, and integration with government systems.
- Communicate technical roadmaps and status updates clearly to senior government officials and departmental executives.
What you need
- Have at least six years of experience as a customer-facing technical or engineering program manager in AI/ML consulting, technology transformation, or enterprise software delivery.
- Possess a strong understanding of enterprise software deployment architectures across cloud, on-premises, hybrid, and air-gapped environments.
- Demonstrate working knowledge or experience with modern AI concepts such as large language models, agentic systems, RAG, fine-tuning, and evaluations.
- Show a proven track record of managing complex, multi-stakeholder technical programs with stringent compliance requirements.
- Hold a bachelor's degree in a relevant field, with advanced degrees or technical certifications considered a plus.
- Be eligible to obtain Canadian government security clearance, with a strong preference for candidates holding an active Top Secret clearance.
Nice to have
- Active Canadian government security clearance such as Secret or Top Secret
- Bilingual English and French proficiency
- Background in Canadian defence, intelligence, or critical infrastructure sectors
- Experience with Government of Canada cloud services or Protected B/C environments
- Project management certification including PMP, PgMP, or government-specific methodologies
Benefits
- Offers Equity
Skills and tech stack
Questions candidates ask
Where is this role located?
Ottawa is required for this position, operating as part of Cohere's customer-facing program management team.
What is the compensation range for the position?
The compensation range for candidates in Canada is CA$200,000 to CA$245,000, and the package includes offers of equity.
What are the security clearance expectations?
An active Top Secret clearance is strongly preferred to enable immediate engagement with sensitive defence accounts. Candidates holding a Secret clearance, those eligible for an upgrade, or those willing to undergo the 12 to 18 month clearance process will also be considered.
What technical background is helpful?
Candidates should have a strong understanding of enterprise software deployment architectures including cloud, on-premises, hybrid, and air-gapped environments. Familiarity with modern AI technologies like LLMs, RAG, fine-tuning, and model inference is also necessary.