Top AI Jobs in Ottawa

Design, build, and operate LLM-facing backend services and evaluation systems. Develop prompts, context pipelines, tool-calling workflows, and retrieval systems. Measure and improve model grounding, consistency, latency, and cost. Ship production-ready solutions and rigorous regression/evaluation pipelines for real-world therapeutic data.

Design, deploy, and operate on-premises AI infrastructure using Kubernetes and Docker. Implement and manage LLM serving (SGLang/vLLM), orchestration (LiteLLM), vector DBs (Milvus), and observability (Langfuse/Prometheus/Grafana). Ensure enterprise security and compliance, collaborate with AI architects and product teams, and deliver documentation and guidance for internal AI platform use.

Senior front-end–leaning full-stack developer to own end-to-end feature delivery across diverse SaaS stacks. Use AI-augmented development tools to accelerate builds, modernize legacy systems, ensure test coverage and safe deployments, mentor junior engineers, and communicate progress to leadership while delivering polished, user-focused UI/UX.

Lead end-to-end feature development and modernization across diverse SaaS stacks, using AI-augmented tooling to accelerate delivery. Maintain legacy production stability, establish testing and secure deployment workflows, and mentor junior engineers while partnering with business stakeholders.

Configure and maintain legal technology platforms, build integrations and automated workflows, develop AI-assisted tools and dashboards, analyze operational data, and drive process improvements across the legal function while collaborating with IT, Product, and AI teams.

The Director of Software Engineering role focuses on enhancing Jobber's AI capabilities, overseeing the integration of intelligent workflows across products to support small business operations more effectively.

As a Senior AI Kernel Engineer, you will design and optimize high-performance kernels for AI inference on GPUs and custom accelerators, improving performance and collaborating with various teams to influence architecture and implementation.

The Technical Product Manager will lead product direction, interface with engineering teams, and ensure the successful deployment of AI-powered safety systems. Responsibilities include defining product vision, translating customer needs, and maintaining high product quality.

Client-facing ML Solutions Architect leading pre-sales, discovery, and design of production-grade ML and agentic AI architectures on AWS. Architect agentic/LLM systems, build POCs, author proposals, advise on build-vs-buy and AgentOps, and mentor delivery teams while ensuring security, cost optimization, and scalable MLOps practices.

Define enterprise AI strategy and architecture for LLMs, RAG, and predictive models; design secure, high-performance REST/GraphQL APIs and event-driven systems; establish AI/data governance; and lead cross-functional teams to productionize real-time AI applications.

As an AI Automations Engineer, you will design and build tooling for GTM, Operations, and Finance teams, automating processes and enhancing systems with a focus on AI.

Design, build, and optimize scalable AI-enabled application features and services. Integrate ML models and generative AI, ensure secure and test-driven implementations, troubleshoot AI performance, mentor engineers, and drive AI architecture, CI/CD, and best practices across teams.

Build and operate large-scale, high-performance infrastructure to run AI inference and agents on real-time streaming data. Design scalable, reliable serving layers, solve distributed-systems challenges, and optimize across cloud providers.

Design and implement end-to-end AI systems and production-grade components. Build and maintain RAG pipelines, backend services, APIs, and data pipelines. Write Python code using Azure AI SDK. Implement document digitization, vectorization, semantic search, and content summarization. Prepare training/evaluation datasets, participate in code reviews, and drive engineering quality and deployment of AI-powered SaaS workflows.

Founding GTM rep responsible for building and qualifying pipeline across enterprises and AI startups, managing inbound requests and outreach automations, re-engaging sign-ups, coordinating discovery calls with founders/CRO, tracking CRM and pipeline metrics, attending events, and proposing GTM experiments and partnerships.

The Account Executive will manage the full sales cycle for enterprise and scale-up accounts, building relationships with technical buyers and collaborating closely with senior leadership to drive revenue and shape sales strategies.

Lead the product strategy for Scribd's internal developer and agentic platforms: unify AI workstreams, own internal app/plugin/agent runtimes, translate functional needs into platform requirements, drive cross-functional adoption and metrics, and run internal rollouts and evaluation to prove impact.

Build and prototype state-of-the-art large language model systems and deep AI assistants, take services from ideation to production, fine-tune and compare open-source and commercial LLMs, use cloud platforms, analyze model and projection accuracy, and collaborate cross-functionally.

Provide embedded legal counsel to product and engineering on privacy, IP, and consumer protection; lead Arena's global privacy program (GDPR, CCPA/CPRA, cross-border transfers); advise on AI governance and responsible deployment; support commercial contracts and data flow frameworks; build privacy processes, playbooks, internal agents, and legal-tech integrations to scale operations.

Lead enterprise product vision and multi-year strategy for integrated product strategy and AI across ABC's portfolio. Build and manage a high-performing product and UX team, define AI-enabled platform and API-first capabilities, partner cross-functionally on go-to-market and technical decisions, and drive platform convergence, monetization, and measurable business outcomes.

Lead global strategic partnerships across cloud, GPU, and hardware providers. Identify and negotiate commercial agreements, manage key partner relationships, align cross-functional stakeholders, build business cases, and support executive strategy to enable Higgsfield's AI infrastructure scale and growth.

The AI/ML Engineer will design and develop AI-powered applications, automate workflows, and integrate AI into BPM's daily operations, ensuring they deliver business value.

Own and scale the Nx-based monorepo, build system, and CI/CD to make builds, tests, and developer workflows fast, reliable, and observable. Build developer tooling, local dev stacks, and production-grade developer infra with SLOs, on-call, and measurable DX improvements.

Lead end-to-end delivery of AI deployments for financial services clients: define features, translate business needs into technical specs, run agile sprints, drive adoption and change management, ensure measurable program outcomes, and expand commercial relationships while collaborating with engineers, product, design, and investment teams.

Design and implement advanced generative AI models, optimize deployment in production, collaborate with teams, and stay updated on AI advancements.