Top AI Jobs in Ottawa

Own new business and account growth across hyperscalers, neoclouds, enterprises, and frontier AI labs in the Americas. Manage complex technical sales cycles, layered OEM/ODM and channel routes, capacity commitments, design-ins, pipeline forecasting, contracts, and executive relationships. Translate semiconductor performance, power, and TCO advantages into commercial outcomes while partnering with product, engineering, marketing, legal, and finance. Build a qualified pipeline through an existing customer network and represent the company at industry events.

As a Principal Data Engineer, you will design and implement LLM, AI-powered security data platforms, mentor engineers, and drive the adoption of data solutions across teams.

Lead technical vision and architecture for AI-powered GTM systems, defining reference architectures, patterns, and governance for low-code and custom agentic solutions. Architect and prototype LLM orchestration, multi-system integrations, RAG pipelines, and event-driven data flows across Salesforce, NetSuite, Marketo, and cloud infrastructure while partnering with GTM leaders to deliver production-grade, auditable, and scalable automation.

Lead end-to-end UX across Babylist web and mobile: run user research, build rapid interactive prototypes, write production front-end code, evolve the design system, instrument outcomes, and champion AI-native design workflows to create intuitive, delightful experiences for families.

Own the company’s AI-powered quality and release infrastructure as its first dedicated hire. Build agent-run test harnesses, LLM graders, regression coverage, release gates, fresh-install and upgrade verification, and natural-language UAT. Manage CI health, artifact publication, deployment pipelines, credentials, certificates, and staging environments. Write production Python code, convert escaped bugs into regression tests, and provide trusted release-readiness evidence through dashboards, runbooks, retrospectives, and operating policies.

Conduct original research on reliable agentic AI, developing methods for simulation, evaluation, optimization, regression control, and continuous learning. Analyze agent failures, traces, and human feedback; create experiments and prototypes; and translate research into production-facing systems. Collaborate with product and engineering teams, contribute to technical strategy, and provide rigorous experimental evidence. The role requires strong research depth, publication or open-source contributions, hands-on Python development, and expertise in LLM agents or agentic systems.

Audit and improve human and model-generated data outputs for accuracy, consistency, and policy compliance. Provide actionable feedback, clarify evolving guidelines, support annotators, coach new team members, monitor workflows and blockers, identify recurring issues and edge cases, participate in calibration discussions, and document findings to improve team performance and quality at scale.

Build and maintain backend AI capabilities for GitLab Duo Chat: design flow components and agentic flows in Python/LangGraph, integrate LLMs and multi-agent orchestration, implement and maintain APIs in the Rails monolith, improve observability and reliability, and participate in on-call rotations and cross-functional collaboration to deliver safe, scalable AI chat features.

Own and improve the AI Social generative media pipeline: build and ship LLM-driven prompts/agent loops, choose and compose media (image, video, voice, music), collaborate with product/design/content, and deliver polished, production-quality social assets.

Lead practical AI adoption across ASIC design, verification, and physical implementation workflows. Develop scalable AI use cases, agent-based solutions, guardrails, and reusable methodologies for engineering teams. Evaluate internal and external AI tools, collaborate with engineering and technology groups, mentor teams, and promote disciplined validation, knowledge sharing, and intellectual property protection.

The VP of Engineering will own engineering strategy, architecture, scaling, hiring, performance management, and people development. This hands-on leader will write and review code, establish technical direction across two pods, develop engineers into technical leads, represent engineering to executives, and partner cross-functionally to prioritize and deliver critical work. Experience in healthcare, HIPAA, or SOC 2 environments is preferred.

Lead Strata from inception as co-founder, defining the vision for regulatory intelligence software, engaging enterprise customers, shaping the product roadmap, providing technical leadership for trusted AI agents, and recruiting teams across go-to-market, product, engineering, and customer success. The role requires early-stage B2B SaaS experience, hands-on LLM and agentic architecture expertise, and the ability to build products emphasizing accuracy, citations, auditability, and expert review.

As a Staff Machine Learning Engineer, you'll lead AI initiatives using large-scale data, optimize ML models for edge devices, and collaborate with cross-functional teams.

Develop and evaluate machine learning and generative AI models using linked genomic and clinical data. Build LLM agentic systems, clinical variant interpretation pipelines, genomic representations, and reliable evaluation workflows. Investigate healthcare data quality, present findings, collaborate with bioinformatics and clinical teams, and contribute to scientific publications. The role requires strong Python, statistics, experimentation, cloud GPU, and software engineering practices, plus interest in biology and precision medicine.

Build and deploy internal AI tooling, agents, integrations, and workflows that improve productivity across engineering, research, and business teams. Evaluate emerging AI tools and models, develop observability and responsible-use guardrails, and partner with stakeholders to prototype and scale solutions. Drive adoption through documentation, enablement, and hands-on support while integrating AI into autonomy, simulation, ML training, and business workflows.

Serve as the technical sales and customer-facing expert for an AI platform. Responsibilities include conducting product demonstrations, supporting proofs of concept, advising on architecture and development, planning professional services projects, tuning retrieval and agentic pipelines, responding to RFPs, supporting customer adoption, and communicating product feedback internally. The role requires strong AI, cloud, on-premise, application development, storytelling, and enterprise customer engagement experience.

Provides technical leadership for agentic AI, ontology, knowledge graph, semantic, and enterprise data platform architecture. Designs reusable data models, ingestion pipelines, integrations, entity resolution, schema alignment, validation, and agent workflows across supply chain systems. Evaluates emerging technologies, establishes architecture and governance standards, mentors teams, and translates research into scalable product capabilities.

Build LanceDB’s revenue marketing function and enterprise demand engine from the ground up. Own account-based marketing strategy, segmentation, campaigns, content, account planning, martech implementation, pipeline reporting, and partner co-marketing. Identify high-intent accounts through open-source and product-usage signals, create tailored omnichannel programs, and collaborate closely with founders, Sales, RevOps, and Partners to source and influence enterprise pipeline.

Serve as the primary technical advisor for SMB sales opportunities, partnering with Account Executives throughout sales cycles. Lead technical discovery, product demonstrations, proof-of-value engagements, competitive evaluations, security questionnaires, RFPs, and technical documentation. Advise IT, security, developer, DevOps, and executive stakeholders on identity, endpoint, SaaS, secrets, cloud, and AI security solutions. Collaborate cross-functionally to improve demos, playbooks, enablement, and customer education.

Partners with AI labs to integrate models, run evaluations, deliver results, and manage customer relationships. Builds pragmatic full-stack solutions, automations, onboarding workflows, and delivery tooling for cutting-edge AI teams. Translates customer and research feedback into product and engineering initiatives, supports strategic account growth, and serves as a technical point of contact across onboarding, releases, and issue resolution.

Own end-to-end AI product development for enterprise clients, from requirements and rapid LLM prototyping through production deployment. Responsibilities include data modeling, ETL pipelines, integrations, evaluation, observability, security, reliability, cost management, and client communication. The role requires shipping real AI products, iterating based on usage, and independently managing ambiguous technical and product decisions.

Build and scale AI-agent infrastructure, including orchestration, tool calling, context management, guardrails, evaluations, and LLM-as-judge pipelines. Develop Python and Node.js microservices, Laravel APIs, AWS infrastructure, and optimized MySQL systems. Diagnose agent failures, improve prompts and tools, maintain reliability and observability, contribute to architecture, review code, collaborate cross-functionally, and mentor engineers.

Partner with executives to understand business operations, identify and prioritize high-impact AI opportunities, define ROI, and create actionable roadmaps. Collaborate with engineers to scope solutions, inform architecture, maintain alignment with business outcomes, present recommendations to C-suite stakeholders, and manage handoffs to implementation.

Leads the vision, strategy, roadmap, team, monetization, governance, and ecosystem growth for ABC Fitness’s API and AI orchestration platform. The role owns developer experience, MCP strategy, access controls, compliance, platform P&L, partner integrations, KPIs, and executive-level cross-functional alignment across product, engineering, security, payments, data, partnerships, and go-to-market teams.

Own paid acquisition across Google, Bing, Meta, and YouTube, scaling campaigns from creative production through launch, optimization, and attribution. Produce high-volume ad assets using AI tools, manage full-funnel campaigns, improve campaign processes, automate repetitive work, and analyze CAC, ROAS, payback, and product activation data. The role requires hands-on Google Ads expertise, creative production skills, subscription funnel experience, and strong ownership in a remote startup environment.