{"id":720974,"url":"https://alion.io/job/shyftlabs-senior-ai-engineer","title":"Senior AI Engineer","company":{"id":685982,"name":"Shyftlabs","domain":"shyftlabs.io","url":"https://alion.io/company/shyftlabs","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"A","score":91,"open_postings":25,"ghost_share":0,"stale_share":0.36,"repost_share":0,"time_to_fill_p50_days":39,"computed_at":"2026-10-28T05:59:10Z"}},"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":["Toronto, Canada"],"countries":["CA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":81000,"max_usd":148000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":74},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Amazon EC2","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"Fine-tuning","optional":false},{"name":"GCP","optional":false},{"name":"GraphQL","optional":false},{"name":"JavaScript","optional":false},{"name":"Kanban","optional":false},{"name":"LLM","optional":false},{"name":"Node JS","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"TypeScript","optional":false},{"name":"Apache Kafka","optional":true},{"name":"ETL/ELT","optional":true}],"status":"live","first_seen_at":"2026-04-21T23:22:31Z","employer_posted_date":"2026-04-21","last_verified_at":"2026-10-28T12:31:46Z","board_verified":true,"closed_at":null,"days_open":189,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":189},"description":"About ShyftLabs\nAt ShyftLabs, we live and breathe data. Since 2020, we've been helping Fortune 500 companies unlock growth with cutting-edge digital solutions that transform industries and create measurable business impact. We're scaling globally with entities in Canada, the U.S., and India and we're looking for passionate problem-solvers who are ready to turn big ideas into real outcomes.\nThe Opportunity\nShyftLabs is looking for a Senior AI Engineer to sit at the intersection of AI/ML engineering and backend platform development. This isn't a research role, it's a hands-on engineering position where you'll design, build, and ship AI-powered features directly into production systems. You'll work closely with Product, Architecture, and cross-functional engineering teams to integrate intelligent capabilities into our next generation of data-driven platforms, while also contributing to the scalable backend infrastructure that powers them.\nThe ideal candidate combines deep AI/ML engineering experience with strong backend development skills, someone equally comfortable fine-tuning an LLM integration as they are designing a robust API or event-driven service.\nWhat You'll Do\nArchitect and implement AI-powered features end-to-end, from model integration and prompt engineering to deployment, monitoring, and iteration\n\nIntegrate LLM APIs, ML models, and intelligent automation pipelines into scalable, production-grade backend systems\n\nFine-tune and optimize models for performance, reliability, and cost efficiency in live environments\n\nDesign and build robust APIs, event-driven services, and third-party integrations that support AI-enabled workflows\n\nCollaborate with Product to translate business requirements into technical AI solutions, defining scope, complexity, and dependencies\n\nBuild and maintain data pipelines and MLOps workflows to support model deployment and lifecycle management\n\nContribute to system architecture decisions, integration patterns, and reusable AI frameworks across the platform\n\nPartner with data scientists and engineers to ensure smooth, scalable model deployments\n\nProduce clear technical documentation, architecture diagrams, data flows, API specs, and AI integration patterns\n\nLead code reviews, enforce best practices in code quality and testing, and mentor engineers across teams\n\nTroubleshoot complex production issues across distributed and AI-integrated systems\n\nStay ahead of industry trends in AI/ML tooling, frameworks, and practices\n\nWhat You Bring\n5+ years of experience building scalable, production-grade software systems\n\n2+ years of hands-on AI/ML engineering experience, including deploying models into production environments\n\nBachelor's degree in Computer Science, Data Science, AI, or a related field\n\nStrong expertise in Python, with hands-on experience using frameworks such as TensorFlow, PyTorch, or Scikit-learn\n\nSolid backend engineering background, API development, microservices, distributed systems, and event-driven architectures\n\nExperience integrating LLM APIs and building AI-driven features into web or platform applications\n\nStrong proficiency in JavaScript/TypeScript and Node.js, with exposure to GraphQL\n\nDeep experience building and consuming RESTful APIs and distributed services\n\nProficiency with SQL and hands-on experience with cloud platforms, GCP or AWS (e.g., S3, Lambda, RDS, EC2)\n\nFamiliarity with MLOps best practices and tools for model monitoring, versioning, and deployment\n\nStrong understanding of software design patterns, system architecture, and data flow design\n\nExcellent communication skills with the ability to articulate complex technical concepts clearly\n\nExperience working in Agile/Kanban environments with a strong grasp of the full SDLC\n\nNice to Have\nExperience with data platforms, analytics systems, or ETL pipelines\n\nFamiliarity with real-time data processing and messaging systems such as Kafka or SQS\n\nExposure to tax, fintech, or compliance-related product development\n\nExperience designing multi-tenant or enterprise-grade SaaS platforms\n\nBackground in integration-heavy environments such as ERP, financial systems, or external data providers\n\nSalary Range\n$120,000 - 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