{"id":4046182,"url":"https://alion.io/job/benevity-senior-ai-systems-engineer","title":"Senior AI Systems Engineer","company":{"id":4677,"name":"Benevity","domain":"benevity.com","url":"https://alion.io/company/benevity","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":92,"open_postings":3,"ghost_share":0,"stale_share":0.333,"repost_share":0,"time_to_fill_p50_days":25,"computed_at":"2026-11-10T06:52:35Z"}},"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":{"min":82900,"max":113960,"currency":"CAD","period":"year","gross":null,"usd_annual":80291},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Embeddings","optional":false},{"name":"Feature Store","optional":false},{"name":"Function Calling","optional":false},{"name":"GCP","optional":false},{"name":"Google ADK","optional":false},{"name":"Hallucination","optional":false},{"name":"LangChain","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Machine Learning","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Scikit-learn","optional":false},{"name":"TensorFlow","optional":false},{"name":"Java","optional":true},{"name":"PHP","optional":true}],"status":"live","first_seen_at":"2026-11-10T20:42:31Z","employer_posted_date":"2026-11-10","last_verified_at":"2026-11-10T23:58:48Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Meet Benevity\nBenevity is the way the world does good, providing companies (and their employees) with technology to take social action on the issues they care about. Through giving, volunteering, grantmaking, employee resource groups and micro-actions, we help most of the Fortune 100 brands build better cultures and use their power for good. We’re also one of the first B Corporations in Canada, meaning we’re as committed to purpose as we are to profits. We have people working all over the world, including Canada, Spain, Switzerland, the United Kingdom, the United States and more!\nBenevity’s software architecture has evolved to include a diverse technology stack. The front-end application, using mainly VueJS, is designed for both desktop and mobile web rendering. Our back-end systems (some Java SpringBoot, some PHP) manage data processing, interfaces with external providers, and ensures robust security. We run and operate our systems in both GCP and AWS cloud, leveraging where possible cloud-native technology. We emphasize clean, maintainable code and use GIT for version control and collaboration. Additionally, our platform integrates with various external services for functionalities like email communication, content storage, and server-to-server interactions.\nOur culture is driven by our core value of “we-are-we” and as a Senior AI Systems Engineer, you will work in an outcome-driven environment where collaboration with your product, design and engineering counterparts is paramount.\nIf you’re eager to make a difference and thrive in a collaborative setting, we invite you to join our team!\nPosition Overview:\nAs a Senior AI Systems Engineer, you'll build and run the machine learning and GenAI systems that power Benevity's products. You'll turn promising prototypes into reliable, production-grade features that help impact leaders do more good. You'll own significant systems from design through monitoring, work closely with data scientists and product managers, and help raise the bar for the engineers around you. You'll work closely with the Staff engineers on architecture and strategy, and lead delivery in your own area.\nWhat you’ll do:\nDesign, build and operate ML and GenAI features end to end, from data ingestion and feature pipelines to model serving and monitoring.\n\nBuild LLM-powered applications such as search, assistants and agents, including RAG pipelines, tool integrations and multi-step workflows.\n\nCreate evaluation frameworks for GenAI systems that combine offline benchmarks, online metrics and human review.\n\nImplement guardrails for GenAI applications, including prompt injection defenses, hallucination mitigation and responsible AI practices.\n\nPut MLOps standards into practice: versioning, automated testing, A/B testing, drift detection and safe rollbacks.\n\nTranslate business problems from product managers and data scientists into clear technical requirements and scoped delivery plans.\n\nWrite design docs, take part in design reviews and give thoughtful code reviews.\n\nMentor mid-level engineers on production ML practices and system design.\n\nBalance latency, cost and quality when choosing models, prompts and infrastructure.\n\nFind and fix bottlenecks in pipelines, serving and platform performance.\n\nWhat you’ll bring:\nBachelor's or Master's degree in Computer Science, Mathematics or a related field, or equivalent professional experience.\n\n5+ years of software engineering experience, including 3+ years building and deploying ML models in production.\n\nHands-on experience across the ML lifecycle: training, evaluation, deployment, monitoring and retraining.\n\nStrong Python skills and experience with ML frameworks such as PyTorch, TensorFlow or scikit-learn.\n\nExperience with at least one major cloud platform (AWS, Azure or Google Cloud) and with distributed workloads.\n\nWorking knowledge of data pipelines, feature engineering and large-scale data processing.\n\nFamiliarity with ML tooling such as experiment tracking, model registries, feature stores or orchestration frameworks.\n\nExperience with CI/CD for ML, including automated validation and rollback strategies.\n\nExperience shipping LLM-based features, including prompt engineering, few-shot techniques and tool or function calling.\n\nExperience building RAG systems, including embeddings, vector databases and retrieval tuning.\n\nExposure to agentic workflows and orchestration frameworks such as LangChain, LlamaIndex or ADK.\n\nSolid grasp of APIs, microservices and reliability fundamentals.\n\nAwareness of data governance, privacy, bias and explainability in AI systems.\n\nClear communication and a collaborative approach with technical and non-technical partners.\n\nGreat-to-haves:\nCertification in relevant cloud platforms or technologies.\n\nDiscover your purpose at work\nWe’re not employees, we’re Benevity-ites. From all locations, backgrounds and walks of life, who deserve more …\nInnovative work. Growth opportunities. Caring co-workers. And a chance to do work that fills us with a sense of purpose.\nIf the idea of working on tech that helps people do good in the world lights you up ... If you want a career where you’re valued for who you are and challenged to see who you can become …\nIt’s time to join Benevity. We’re so excited to meet you.\nWhere We Work\nAt Benevity, we embrace a flexible hybrid approach to where we work that empowers our people in a way that supports great work, strong relationships, and personal well-being. For those located near one of our offices, while there’s no set requirement for in-office time, we do value the moments when coming together in person helps us build connection and collaboration. Whether it’s for onboarding, project work, or a chance to align and bond as a team, we trust our people to make thoughtful decisions about when showing up in person matters most.\nJoin a company where DEIB isn’t a buzzword\nDiversity, equity, inclusion and belonging are part of Benevity’s DNA. You’ll see the impact of our massive investment in DEIB daily - from our well-supported employee resources groups to the exceptional diversity on our leadership and tech teams.\nWe know that diverse backgrounds, experiences, skills and passions are what move our business and our people forward, so we're committed to creating a culture of belonging with equal opportunities for everyone to shine.\nThat starts with a fair and accessible hiring process. 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