{"id":101902,"url":"https://alion.io/job/resmed-senior-ai-engineer-platform-engineering","title":"Senior AI Engineer, Platform Engineering","company":{"id":99683,"name":"ResMed","domain":"resmed.co.uk","url":"https://alion.io/company/resmed-2","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":80,"open_postings":45,"ghost_share":0,"stale_share":0.8,"repost_share":0.022,"time_to_fill_p50_days":37,"computed_at":"2026-10-17T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Halifax, Canada"],"countries":["CA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":71000,"max_usd":129000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":56},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"AWS Strands Agents","optional":false},{"name":"Confluence","optional":false},{"name":"Context Engineering","optional":false},{"name":"Datadog","optional":false},{"name":"Embeddings","optional":false},{"name":"Function Calling","optional":false},{"name":"GitHub","optional":false},{"name":"Go","optional":false},{"name":"Hybrid Search","optional":false},{"name":"Jira","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"OpenAI Agents SDK","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Reranking","optional":false},{"name":"Slack","optional":false},{"name":"Structured Outputs","optional":false},{"name":"Tool Use","optional":false},{"name":"TypeScript","optional":false},{"name":"LangChain","optional":true},{"name":"Langfuse","optional":true},{"name":"Model Context Protocol","optional":true},{"name":"OpenSearch","optional":true}],"status":"live","first_seen_at":"2026-06-24T00:00:00Z","employer_posted_date":"2026-06-24","last_verified_at":"2026-10-17T07:25:24Z","board_verified":true,"closed_at":null,"days_open":115,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":115},"description":"Global Technology Solutions (GTS) at ResMed is a division dedicated to creating innovative, scalable, and secure platforms and services for patients, providers, and people across ResMed. The primary goal of GTS is to accelerate well-being and growth by transforming the core, enabling patient, people, and partner outcomes, and building future-ready operations.\nThe strategy of GTS focuses on aligning goals and promoting collaboration across all organizational areas. This includes fostering shared ownership, developing flexible platforms that can easily scale to meet global demands, and implementing global standards for key processes to ensure efficiency and consistency.\nAbout the Role:\nWe are seeking a Senior AI Engineer - Platform Engineering to design, build, and deploy intelligent agent-based solutions that solve business and engineering problems.\nYou will leverage cloud-native and AI platform capabilities to develop production-grade AI applications, autonomous workflows, and Retrieval-Augmented Generation (RAG) solutions that improve productivity, automate complex processes, and enhance decision-making across the organization.\nThis role requires a strong blend of software engineering, AI application development, systems integration, and solution architecture. The ideal candidate has hands-on experience building AI agents, Retrieval-Augmented Generation (RAG) solutions, and tool-driven workflows using modern LLM frameworks.\nResponsibilities:\nDesign, build, and deploy AI agents and agentic workflows that solve business and engineering challenges using modern LLM frameworks.\nDevelop AI-powered applications leveraging Retrieval-Augmented Generation (RAG), vector databases, embeddings, tool calling, and agent orchestration patterns.\nOptimize retrieval quality and response accuracy through chunking strategies, metadata enrichment, hybrid search, reranking, evaluation, and continuous improvement.\nIntegrate AI solutions with enterprise platforms such as GitHub, Jira, Confluence, Datadog, Slack, Kubernetes, and internal APIs.\nDevelop reusable connectors, tools, and agent capabilities that enable agents to retrieve information and perform actions across systems.\nEstablish best practices for testing, evaluation, observability, security, and governance of AI applications.\nMonitor and optimize agent performance, reliability, latency, accuracy, and cost while troubleshooting production issues and continuously improving solution quality. Required Qualifications:\n5+ years of experience in Software Engineering, Platform Engineering, or Cloud Engineering\nHands-on experience building AI applications using frameworks such as LangGraph, Strands Agents, OpenAI Agents SDK, or similar agent orchestration frameworks.\nStrong programming skills in TypeScript, Go and/or Python\nExperience designing and building microservice applications\nExperience integrating APIs and enterprise systems\nHands-on experience building production AI applications using LLMs Strong understanding of:\nRetrieval-Augmented Generation (RAG)\nVector databases and embeddings\nTool calling and agent orchestration\nStructured outputs, context engineering, and agent orchestration\nAI evaluation and observability Preferred Qualifications:\nExperience building AI copilots, digital assistants, or autonomous agents\nExperience integrating AI solutions with GitHub, Jira, Slack, Datadog, Confluence, or similar enterprise platforms\nExperience with vector databases such as OpenSearch\nExperience with AI observability and evaluation tools such as Langfuse or Datadog LLM Observability\nExperience building MCP servers and agent interoperability patterns\nExperience with Kubernetes and cloud-native platforms What Success Looks Like:\nDeliver production-ready agentic AI solutions that solve real business and engineering challenges\nBuild reusable AI workflows, tools, and integrations that accelerate adoption across teams\nImprove productivity and operational efficiency through intelligent automation\nDrive measurable outcomes through scalable, secure, and reliable AI applications\nJoining us is more than saying “yes” to making the world a healthier place. It’s discovering a career that’s challenging, supportive and inspiring. Where a culture driven by excellence helps you not only meet your goals, but also create new ones. We focus on creating a diverse and inclusive culture, encouraging individual expression in the workplace and thrive on the innovative ideas this generates. If this sounds like the workplace for you, apply now! 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