{"id":2864457,"url":"https://alion.io/job/safe-fleet-senior-software-engineer-ai-product-engineering","title":"Senior Software Engineer, AI Product Engineering","company":{"id":2875979,"name":"Safe Fleet","domain":"safefleet.net","url":"https://alion.io/company/safefleet-net","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Comeet","truth_index":{"grade":"B","score":75,"open_postings":6,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":30,"computed_at":"2026-10-20T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Coquitlam, Canada"],"countries":["CA"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":120000,"max":140000,"currency":"CAD","period":"year","gross":null,"usd_annual":99349},"salary_estimate":null,"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Claude","optional":false},{"name":"Claude Code","optional":false},{"name":"Computer Vision","optional":false},{"name":"Copilot","optional":false},{"name":"Cursor","optional":false},{"name":"GCP","optional":false},{"name":"Gemini","optional":false},{"name":"Machine Learning","optional":false},{"name":"OpenAI","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"RAG","optional":false},{"name":"Agile","optional":true},{"name":"CI/CD","optional":true},{"name":"Hugging Face","optional":true},{"name":"Model Context Protocol","optional":true}],"status":"live","first_seen_at":"2026-10-19T16:02:48Z","employer_posted_date":"2026-10-19","last_verified_at":"2026-10-20T09:10:27Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Description\nABOUT THE POSITION\nMeet the Smart Safety Company\nAt Safe Fleet our name says it all. We make fleet vehicles - and everyone in and around them - safer. Our fleet safety platform brings together best-in-class products, ground-breaking technology, and a 100-year history of fleet know-how and innovation to solve the world’s biggest fleet safety problems.\nOur core value is safety. Without safety first, efficiency and productivity are not possible. This is true for our products, our culture, and our relationship with our community. Our vision is to reduce preventable deaths and injuries in and around fleet vehicles with a goal of ZERO accidents.\nWe are re-defining what safety means for fleets of every type - from school buses to waste collection trucks, firefighting to utility vehicles, police cruisers to delivery vans.\nWhether you work in our Charlotte plant to build life-saving stop arms for school buses, or design advanced camera vision products in our Vancouver office, forge valves and high-quality nozzles to fight fires, or dream up new ways to protect fleet operators in our Corporate HQ in Kansas City, you’ll contribute to our goal to keep everyone safe.\nWe are a fast-growing manufacturing, service, and technology company with over 1700 employees in over 15 locations across Canada and the US. We’re looking for motivated self-starters with innovative thinking to join our team and help us achieve our growth and performance goals. Sound like you?\nJOB SUMMARY\n\nWe are seeking a highly skilled, hands-on Senior Software Engineer to design, develop, and deliver AI-powered features and capabilities across our product portfolio.\nThe ideal candidate combines strong software engineering fundamentals, practical expertise in modern AI technologies, and experience delivering production-grade AI solutions. The role requires proficiency in AI-Native Engineering and Agentic SDLC, leveraging AI coding agents, Spec-Driven Development, and automation to accelerate software delivery while maintaining high standards of quality and security.\nThis is a hands-on engineering role focused on building scalable AI solutions that deliver measurable customer value.\nYou will\n\nAI Product Engineering\nDesign, develop, and deploy scalable, secure, and production-ready AI features and shared AI services. \nApply Generative AI, Machine Learning, Deep Learning, and Computer Vision to solve product challenges. \nBuild solutions using LLMs, RAG, AI agents, workflow orchestration, and traditional Machine Learning techniques. \nDevelop robust backend services and APIs to integrate AI capabilities into existing products. \nImplement AI evaluation, monitoring, and optimization to ensure reliability, performance, and cost efficiency. \nContribute to reusable AI architecture patterns, technical prototyping, and production delivery. \nAI-Native Engineering & Agentic SDLC\nApply AI-Native Engineering practices throughout the software development lifecycle. \nLeverage AI coding agents, Spec-Driven Development (SDD), and development automation to improve engineering productivity. \nDevelop and utilize AI agents, reusable skills, and automated workflows for implementation, testing, code review, and delivery. \nContinuously improve Agentic SDLC practices while maintaining software quality, security, and maintainability. \nCollaboration & Continuous Improvement\nCollaborate with Product Management and other engineering teams to translate product requirements into technical solutions. \nParticipate in architecture and design discussions, code reviews, and technical decision-making. \nMentor other engineers and contribute to engineering standards, technical knowledge sharing, and continuous improvement. \nStay current with emerging AI technologies and AI-Native Engineering best practices. \nSalary: $120,000 - $140,000/yr CAD + 12.5% bonus\nThe final offer will be determined based on a combination of factors including skills, experience, and alignment with the role’s responsibilities.\nCandidates at the lower end of the range will meet the core qualifications and demonstrate strong potential to grow within the role.\nMid-range offers reflect a solid match with the role’s technical and collaborative requirements.\nOffers at the top of the range are reserved for candidates who bring exceptional qualifications, specialized expertise, or unique value that significantly exceeds the baseline expectations\nAt Safe Fleet, we are an equal opportunity employer that is committed to creating a diverse and inclusive workplace where everyone is valued and respected. We embrace diversity and do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or any other legally protected status. We promote fair and equitable hiring practices and foster a culture of inclusivity and respect. Our core values of integrity, innovation, teamwork, customer focus, and safety guide our efforts to provide a workplace where all employees can thrive and reach their full potential.\nRequirements\n6+ years of professional software engineering experience, including strong system design and software architecture skills. \nProven hands-on experience developing and deploying AI-powered applications or product features in production. \nStrong experience with modern AI platforms and services, such as OpenAI, Azure OpenAI, Google Gemini, Claude, or equivalent technologies. \nSolid understanding of LLMs, transformer-based models, prompt engineering, RAG architectures, AI agents, and workflow orchestration. \nPractical knowledge of Data Science and Machine Learning fundamentals, including model evaluation and performance considerations. \nStrong experience developing backend systems, APIs, and scalable cloud-based solutions using AWS, Azure, or GCP. \nProficiency with AI coding agents, such as Claude Code, GitHub Copilot, Cursor, or equivalent tools. \nHands-on experience applying AI-Native Engineering practices, including Spec-Driven Development and AI-assisted software development workflows. \nPractical understanding of Agentic SDLC, including agent-assisted implementation, automated testing, verification, and development automation. \nStrong problem-solving, communication, and cross-functional collaboration skills. \nPreferred Qualifications\nExperience developing AI-powered features for commercial software products. \nExperience with Computer Vision, image/video analytics, Deep Learning, or predictive Machine Learning. \nExperience with local/self-hosted models, Hugging Face, and Model Context Protocol (MCP). \nExperience with AI agent orchestration frameworks and production ML pipelines. \nExperience developing custom AI coding agents, reusable agent skills, automated verification, and CI/CD integration. \nExperience building reusable AI services or shared AI platforms. 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