{"id":50660,"url":"https://alion.io/job/expel-senior-ai-platform-engineer","title":"Senior AI Platform Engineer","company":{"id":11770,"name":"Expel","domain":"expel.com","url":"https://alion.io/company/expel","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":142900,"max":207200,"currency":"USD","period":"year","gross":null,"usd_annual":207200},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon EKS","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"AWS Bedrock AgentCore","optional":false},{"name":"AWS Step Functions","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Python","optional":false},{"name":"CI/CD","optional":true},{"name":"Function Calling","optional":true},{"name":"GCP","optional":true},{"name":"PyTorch","optional":true},{"name":"RAG","optional":true},{"name":"Scikit-learn","optional":true},{"name":"Spark","optional":true},{"name":"TensorFlow","optional":true},{"name":"Vertex AI","optional":true}],"status":"closed","first_seen_at":"2026-08-11T00:00:00Z","employer_posted_date":null,"last_verified_at":"2026-10-10T00:00:30Z","board_verified":false,"closed_at":"2026-10-10T00:00:30Z","days_open":60,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":60},"description":"You believe great ML systems don't just work - they scale, they recover gracefully, and they give data scientists the confidence to iterate quickly. At Expel, you'll be a key contributor in building and maturing the infrastructure that powers our machine learning and generative AI capabilities. From end-to-end training pipelines to the specialized infrastructure behind production agentic applications, your work will directly shape how fast we can innovate and how reliably our AI systems run.\nYou'll work closely with senior and principal engineers, data scientists, and cross-functional teams to operationalize ML at scale. You bring strong hands-on expertise and a genuine drive to continuously improve the systems and practices around you.\n What Expel can do for you\nGive you hard, meaningful problems - building the infrastructure that lets defenders win using AI\nConnect you with a collaborative team of engineers, data scientists, and researchers who care about doing it right\nOffer unlimited PTO (that leadership models and encourages), up to 24 weeks of parental leave, and really excellent health benefits\nPay you a monthly fitness and cell phone stipends - no receipts required\nSupport your professional growth with a conference benefit and continuous learning opportunities\nOffer full remote flexibility - work from wherever you do your best work\n What you can do for Expel\nBuild and scale ML infrastructure\nArchitect and maintain end-to-end machine learning training pipelines on AWS (SageMaker, EKS, Step Functions) to ensure reliable and reproducible model development and deployment\nBuild and maintain infrastructure for production agentic applications using Amazon Bedrock and Bedrock AgentCore - including agent runtimes, memory, secure gateways, and observability at scale\nContribute to the architectural evolution of our ML platform, including evaluating MLOps tooling and participating in buy vs. build decisions\nOperationalize with rigor\nImplement AI/ML governance best practices for model versioning, testing, validation, maintenance, and security\nIntegrate MLOps best practices with Expel's SDLC, security, and infrastructure standards, working alongside SRE, Platform Engineering, and Security teams\nDrive quality, reliability, and scalability improvements through thoughtful engineering and monitoring\nCollaborate and enable\nPartner with data scientists, software engineers, and stakeholders to operationalize ML models reliably and at scale\nMentor and support junior engineers; foster a culture of engineering excellence\nCreate and maintain documentation, internal tooling, and enablement resources so practitioners across Expel can work effectively with ML systems\nStay current with the MLOps landscape and bring relevant innovations back to the team\n What you should bring with you\nCollaboration & communication\nClear communicator - able to write documentation and explain technical concepts to both engineering and non-technical audiences\nStrong collaborator with engineers, product managers, and business stakeholders\nDemonstrated ability to mentor others and invest in the growth of the people around you\nBalances near-term delivery with longer-term technical quality\nTechnical depth\nStrong Python proficiency; familiarity with other languages (Go, JS) is a plus\nSolid experience with CI/CD pipelines, infrastructure-as-code, and containerization for ML workloads\nHands-on experience with cloud-based ML platforms - AWS (SageMaker, Bedrock, Bedrock AgentCore) strongly preferred; GCP (Vertex AI) experience also valued\nProven experience operationalizing LLMs and building infrastructure for complex agentic applications - agent orchestration, memory, tool calling, RAG architectures\nFamiliarity with ML frameworks including Scikit-Learn, PyTorch, Spark, and TensorFlow\nWorking knowledge of continuous retraining, concept drift monitoring, and data drift detection in production\nEducation & experience\n5+ years of relevant software engineering experience with meaningful focus on ML operations and infrastructure\nDegree in Computer Science, Mathematics, Statistics, Engineering, or a related technical field preferred (or a compelling story)\nDemonstrated track record of delivering impactful ML infrastructure or MLOps projects\nExperience contributing to team practices, standards, or tooling in a collaborative environment\n Additional information\nThe base salary range for this role is between $142,900 USD and $207,200 USD + bonus eligibility and equity.\nWe believe in paying transparently and equitably. Your salary will ultimately be based on factors such as your experience, skills, team equity, and market data. You’ll also be eligible for unlimited PTO (which we model and encourage), work location flexibility, up to 24 weeks of parental leave, and really excellent health benefits.\nWe’re only hiring those authorized to work in the United States.\nWe’re an Equal Opportunity Employer: You’ll receive consideration for employment without regard to race, sex, color, religion, sexual orientation, gender identity, national origin, protected veteran status, or on the basis of disability.\nWe will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.\nSalary Range\n$142,900-$207,200 USD","description_format":"text","description_chars":5450,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Continuous learning","Equity","Parental leave","Unlimited PTO"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Cybersecurity","Security Operations","Managed Security"],"lifecycle":[{"event":"open","at":"2026-08-11T00:00:00Z"},{"event":"expire","at":"2026-10-10T00:00:30Z"}],"visa":[],"liveness":null,"pay":{"stated_usd_annual":207200,"is_top_pay":true},"html_url":"https://alion.io/job/expel-senior-ai-platform-engineer","json_url":"https://alion.io/job/expel-senior-ai-platform-engineer.json","meta":{"generated_at":"2026-10-11T22:20:22Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":12042,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-12T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":11770},"rest":"https://alion.io/mcp/rest/get_company?id=11770"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fexpel-senior-ai-platform-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fexpel-senior-ai-platform-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fexpel-senior-ai-platform-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/expel-senior-ai-platform-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fexpel-senior-ai-platform-engineer"}]}