Jobs at Raydar

Leads the engineering organization by hiring, coaching, and managing engineers; setting technical direction; improving delivery practices; and ensuring reliable software releases. Oversees customer applications, internal tools, data, payments, and IT systems. Designs AI-driven workflows to reduce manual effort, makes architecture decisions, contributes code when needed, and collaborates with product partners. The role also leads engineering, QA, and design staff in a hybrid Toronto environment.

Develop geometry and CAD software that matches and validates 3D models against 2D drawings. Contribute to geometry libraries and design tools, extend a toolpath computation engine, investigate geometric algorithms, and eventually own a core software subsystem from design through maintenance. The role applies mathematical and low-level software expertise to physical manufacturing and requires solving loosely defined computational problems.

Build and maintain full-stack web applications, develop internal production tools, gather feedback from shop-floor users, and iterate on solutions. The role requires ownership of platform uptime, including responding to outages and restoring service. Engineers will work closely with machinists and mechanical engineers in an on-site manufacturing environment to identify operational problems and deliver practical software improvements.

Advise legal-sector decision-makers on adopting an AI-powered product through consultative meetings, tailored demonstrations, pilot design, outcome measurement, and rollout support. Partner with sales, product, marketing, and customer success teams to communicate customer insights, shape product strategy, develop messaging, and support go-to-market efforts. The role requires legal expertise, familiarity with Toronto law firms, strong communication skills, and frequent client engagement in the Toronto area.

Embed with portfolio companies to identify high-impact workflows, build and deploy agentic software integrations, prompts, evaluations, and user interfaces, then tune systems in production. Serve as the technical partner to business leaders, manage end-to-end outcomes, and codify successful patterns into reusable playbooks. The role requires full-stack development, production LLM experience, strong stakeholder communication, startup experience, and frequent travel to portfolio companies.

Convert inbound leads into signed legal client engagements while meeting personal revenue targets. Advise prospective clients, manage and forecast the sales pipeline, create sales and onboarding materials, mentor junior lawyers, and collaborate with product and engineering teams to automate intake and follow-up. The role requires daily use of generative AI tools and consultative sales skills.

Advise prospective clients, assess their legal circumstances, explain options, and guide them from initial consultation through signed retainer. Own client relationships, meet revenue targets, use AI tools to manage research and follow-up, test internal tools, report issues to engineering, and create playbooks and training materials.

Build and deploy AI-driven software for operating businesses, including integrations, prompts, evaluation tools, and user interfaces. Own delivery from workflow discovery through launch, tuning, and handoff. Partner directly with business leaders, manage expectations, develop reusable deployment playbooks, and serve as a trusted technical contact. The role requires full-stack engineering, production LLM or agent experience, customer-facing collaboration, strong communication, and frequent travel to client sites.

Lead product and engineering for a client-facing software platform. Own technical direction, architecture, product roadmap, user experience, and AI-driven workflow development. Build a scalable platform, prioritize stakeholder requests, hire and develop cross-functional technology talent, and remain hands-on with coding. The role requires hybrid work in Toronto three days per week and offers leadership responsibility across multiple business functions.

Own and expand the partnerships function, growing partnership revenue, developing platform integrations and professional services channels, and building a high-performing partnerships team. The role manages partner relationships, defines product requirements with engineering and executives, drives adoption of embedded partner offerings, evaluates commercial economics, and recruits team members. This is a hybrid position based in Toronto.

Builds and ships production code, customer integrations, data pipelines, and analytics tools for enterprise accounts. Serves as the technical lead for several clients, gathering requirements, prototyping solutions, owning system performance and service levels, and communicating with technical and executive stakeholders. The role requires hands-on software engineering, cloud and data-platform experience, schema design, production monitoring, and approximately 30% travel to customer sites across the United States.

Own the production deployment and optimization of machine learning models at high request volumes. Responsibilities include reducing inference latency, improving throughput, profiling GPU code, containerizing models, designing distributed multi-GPU serving systems, and applying quantization, batching, caching, compression, and knowledge-transfer techniques. The role requires strong systems programming, GPU optimization, distributed systems, container orchestration, and production software experience.

Manages a small engineering team delivering a customer-facing product while contributing hands-on code. Responsibilities include technical design, roadmap planning, hiring, coaching, incident response, release reliability, and initiatives involving performance, analytics, experimentation, real-time data syncing, and generative AI workflows.

Lead the strategy and hands-on development of platform-wide design systems, including scalable interaction patterns, UX frameworks, mobile experiences, and AI-driven design-quality tools. Partner with engineers, product managers, and designers to improve design consistency and implementation quality across complex B2B products. Own initiatives from problem identification through prototyping and delivery while maintaining strong visual, interaction, accessibility, and code-adjacent design craft.

Manage Canadian immigration matters across economic, provincial nominee, family, work permit, and inadmissibility files. Counsel clients throughout applications, represent them when needed, and use AI tools to improve legal workflows and client service. The role offers potential progression into leadership or managing attorney responsibilities and requires Canadian legal licensure, immigration law experience, Canadian work authorization, and availability during Eastern Time hours.

Build and ship full-stack conversational AI features, integrating speech recognition, text-to-speech, and large language models into reliable production systems. Improve latency, reliability, cost, developer experience, and platform foundations at enterprise scale. Collaborate with product and machine learning teams, own initiatives end to end, incorporate production feedback, and support customer-facing engineering work.

Own and improve CI/CD, developer tooling, agent harnesses, Kubernetes infrastructure, observability, cost management, and incident-response practices. Build platform capabilities that reduce engineering toil and improve delivery speed for conversational AI products. Participate in an on-call rotation for core infrastructure and help shape reliable, scalable systems across a fully remote engineering organization.

Own and evolve the company’s visual identity across web, campaigns, social, sales collateral, events, and merchandise. Translate complex voice AI concepts into clear diagrams, illustrations, and marketing graphics. Build scalable brand systems, templates, and standards while partnering with product, marketing, and executive teams. Execute hands-on across digital, print, and experiential media with limited direction and high craft.

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.