Top AI Jobs in Ottawa

The Software Engineer will develop backend systems for an AI Energy Agent, including data integration, microservices, and scalable architecture, focusing on performance and reliability.

The AI-Native Data Engineer will build data pipelines, architect databases, design GCP infrastructure, and automate workflows for energy management using AI.

As a Founding AI Engineer, you will develop an AI-powered knowledge platform, focusing on backend systems, machine learning data pipelines, and optimizing tech stack for performance while participating in the entire product lifecycle.

As a Chatdesk Expert, provide customer support for brands through social media and email. Set your own schedule and work remotely.

The AI Engineer will design, develop, and deploy AI-powered systems, improve operations with intelligent workflows, and collaborate on high-leverage AI opportunities.

Lead and scale Mimica's product organisation, define global product strategy and roadmap for AI-driven task/process mining and automation, mentor product and design teams, improve product operations and discovery, align cross-functional stakeholders, handle escalations, and hire and forecast team needs.

Lead architecture and evolution of Juniper Square’s distributed services, cloud infrastructure, and developer platform. Design scalable, multi-tenant, event-driven systems; build paved-road developer tooling, CI/CD, and observability. Hands-on coding, prototyping, and performance troubleshooting. Enable production AI/LLM workloads, ensure security/compliance, support enterprise upmarket needs, and mentor engineering teams to raise operational excellence and reliability.

Lead design, build, and automation of AWS infrastructure using Terraform; create and improve CI/CD pipelines; support a multi-tenant SaaS platform for reliability and security; integrate AI tooling, AI agents, and MCP servers into DevOps workflows to boost delivery speed and reduce toil; establish monitoring, access control, and operational best practices; collaborate with cross-functional teams and communicate with stakeholders.

Design, build, and productionize LLM-powered applications and agentic AI systems. Develop data and inference pipelines, deploy and monitor models, define evaluation frameworks, optimize performance/cost, and enforce governance, safety, and observability to deliver scalable AI-driven customer experience solutions.

Lead technical strategy and execution for Merlin's AI Core platform across perception, sensor fusion, planning, and control. Build and manage a multidisciplinary engineering organization, own architecture from data pipelines to real-time onboard inference, enforce aviation-grade safety and quality, partner with certification and systems teams, recruit senior talent, and translate research into product opportunities.

Develop and deploy generative AI and LLM solutions end-to-end for e-commerce: research models, build ETL/data pipelines, run distributed training and experiments, collaborate with product and engineering to deliver production systems that improve recommendations, search, personalization, and customer interactions.

Support Data Science and Regulatory Affairs to define and execute regulatory strategies for AI/ML-enabled medical devices. Translate ML concepts into regulatory documentation, create DHF and submission materials (510(k), EU MDR, Health Canada), maintain dataset and model documentation, and manage version control and change management.

Founding research hire to develop clinical reasoning and computer-use models using proprietary hospital and clinic data. Own end-to-end training and evaluation pipelines, design benchmarks exposing LLM weaknesses on clinical reasoning, run experiments, and publish technical reports and papers. Collaborate closely with founders and deploy research into products that improve physician workflows.

Design, build, and ship end-to-end AI and data solutions using proprietary data infrastructure. Scope projects with business stakeholders, implement models, pipelines, and APIs (Python/SQL), deploy on Snowflake or BigQuery, and iterate post-launch. Enable non-technical teams, collaborate with Data Engineering and AI teams, and operationalize LLMs, embeddings, and predictive models into working internal products.

Ship real open-source integrations and MCP servers to bring SearchApi to agent and automation frameworks. Create PRs, example apps, docs, and integration guides. Stay current with the agent ecosystem, pick high-leverage targets, and work independently to deliver production-ready integrations.

The Senior Staff AI Engineer will lead the design and optimization of reinforcement learning systems for enterprise applications, focusing on scalable architectures and production deployment. Responsibilities include mentoring, collaboration, and ensuring compliance with AI ethics and safety standards.

The role involves end-to-end machine learning lifecycle management, including data processing, model development, rigorous testing, and production deployment, focusing on large quantitative models for AI-first products.

The Machine Learning Engineer will manage the ML lifecycle, develop models, ensure performance, and collaborate with a diverse team to build AI-first products.

The AI/ML Engineering Manager leads ML engineering teams, manages client engagements, shapes architecture, ensures technical quality, and drives business growth through ML operations.

Design and deliver enterprise-grade AI/GenAI solutions on Salesforce or ServiceNow. Lead RAG pipelines, LLM workflows, NLP automation, and vector retrieval integrations. Architect scalable API/microservice integrations, ensure performance, security, and reliability, and define AI governance and guardrails. Collaborate with product, engineering, and customers through discovery, workshops, and demos to operationalize AI for Field and Customer Service workflows.

Design, build, deploy, and operate an internal AI platform and AI-powered developer workflows. Implement CI/CD for models, prompts, and evaluations; integrate Bedrock/agent frameworks; ensure security, observability, reliability, and cost/version controls; respond to incidents and participate in on-call rotations; promote AI best practices and lead architecture discussions.

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 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 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.

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.