{"id":1293915,"url":"https://alion.io/job/givzey-ai-platform-engineer","title":"AI Platform Engineer","company":{"id":2077569,"name":"Givzey","domain":"givzey.com","url":"https://alion.io/company/givzey","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Breezy","truth_index":{"grade":"B","score":75,"open_postings":4,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-09-29T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":137000,"max_usd":244000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":222},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon CloudWatch","optional":false},{"name":"Amazon ECS","optional":false},{"name":"Amazon S3","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"AWS Lambda","optional":false},{"name":"CI/CD","optional":false},{"name":"CloudFormation","optional":false},{"name":"Docker","optional":false},{"name":"GitHub Actions","optional":false},{"name":"IAM","optional":false},{"name":"LLM","optional":false},{"name":"OpenSearch","optional":false},{"name":"Pulumi","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Terraform","optional":false},{"name":"Dagster","optional":true},{"name":"New Relic","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Redis","optional":true},{"name":"SOC 2","optional":true}],"status":"live","first_seen_at":"2026-07-07T17:38:08Z","employer_posted_date":"2026-07-07","last_verified_at":"2026-09-29T22:20:36Z","board_verified":true,"closed_at":null,"days_open":84,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":84},"description":"About Givzey / Version2.ai\nJoin the Future of Fundraising at Givzey!Givzey is one of the fastest-growing and most innovative technology companies serving the nonprofit sector, on a mission to unlock more generosity through AI-powered donor engagement. At the center of that innovation is Version2.ai, the world’s first Autonomous AI fundraisers-Virtual Engagement Officers (VEOs)-designed to independently manage donor engagement and generate revenue. Unlike traditional AI tools that simply make staff more efficient, VEOs expand fundraising capacity by acting as AI workers that operate donor portfolios, build relationships, and secure gifts on their own. In just three years, Givzey’s platform has already helped organizations raise $10M+ through autonomous engagement, including individual gifts as large as $100,000. Alongside this breakthrough technology, Givzey’s Gift Agreement Platform modernizes the multi-year giving process, enabling nonprofits to secure, manage, and forecast commitments with unprecedented ease.\nAbout the role\nThis role owns the platform that keeps Givzey secure, compliant, reliable, and scalable. You'll work across AWS infrastructure, Infrastructure as Code, CI/CD, AI services, observability, and developer tooling to make sure engineers spend their time building product instead of fighting deployments.\nYou'll partner closely with engineering, ML, and product to design the platform that powers everything from customer-facing APIs to LLM workflows running on Amazon Bedrock and SageMaker.\nThis is not a \"keep the lights on\" devops role. You'll actively shape how we deploy software, provision infrastructure, manage AI workloads, and scale the engineering organization.\nWho thrives here\nYou're the engineer who gets excited about replacing a manual deployment with a one-click pipeline, automating infrastructure instead of clicking around the AWS console, and designing systems that make the rest of engineering move faster.\nYou think in terms of reliability, observability, automation, and repeatability.\nYou're comfortable wearing multiple hats. One morning you might be debugging IAM permissions. That afternoon you're building a Pulumi module, improving GitHub Actions, tuning ECS workloads, or helping an ML engineer deploy a SageMaker endpoint.\nWhat you'll do\nCloud infrastructure\nDesign, build, and maintain our AWS infrastructure\nManage networking, IAM, compute, storage, databases, and security across environments\nBuild scalable infrastructure capable of supporting rapid product growth\nImprove resiliency, availability, and disaster recovery\nInfrastructure as Code\nOwn our Infrastructure as Code strategy using Pulumi\nBuild reusable infrastructure components and shared modules\nEliminate manual infrastructure changes wherever possible\nReview and evolve our cloud architecture as the company grows\nCI/CD\nBuild and maintain deployment pipelines for applications and infrastructure\nImprove release automation and deployment safety\nReduce friction in local development and engineering workflows\nHelp establish engineering best practices around testing and deployment\nAI Platform\nBuild and maintain the infrastructure powering our AI systems\nWork with services such as Amazon Bedrock, SageMaker, OpenSearch, and supporting AWS services\nSupport LLM evaluation pipelines, RAG infrastructure, vector search, and model deployment\nPartner with ML engineers to operationalize new AI capabilities\nPlatform Operations\nMonitor production systems and improve observability\nRespond to production incidents and drive root-cause analysis\nImprove system reliability through automation rather than manual processes\nContinuously evaluate performance, cost, and scalability\nEngineering\nCollaborate closely with product, engineering, ML, and customer success\nHelp define technical standards and infrastructure direction\nParticipate in architecture discussions across the platform\nMentor other engineers on cloud infrastructure and operational best practices\nWhat we're looking for\nExperience\n5+ years building and operating production software systems\nStrong experience with AWS in production environments\nExperience designing Infrastructure as Code using Pulumi, Terraform, or CloudFormation\nExperience building CI/CD pipelines using GitHub Actions\nStrong Python experience\nExperience building APIs and backend systems\nCloud & Platform\nYou should be comfortable working with technologies such as:\nAWS (multi-account environments using AWS Organizations)\nECS \nDocker\nIAM\nVPC networking\nRDS\nS3\nLambda\nCloudWatch\nSNS/SQS\nEvent-driven architectures\nAI Infrastructure\nExperience with some of the following is highly desirable:\nAmazon Bedrock\nSageMaker\nVector databases\nRetrieval-Augmented Generation (RAG)\nLLM evaluation pipelines\nModel deployment\nML infrastructure\nDagster or similar orchestration platforms\nWorking Style\nYou automate repetitive work instead of documenting it.\nYou care about reliability as much as shipping features.\nYou enjoy improving developer experience.\nYou think systems should become simpler over time.\nYou take ownership rather than waiting for someone else to fix infrastructure problems.\nMindset\nStrong written communication.\nComfortable working in ambiguity.\nCurious about modern AI infrastructure and where it's headed.\nInterested in building systems that engineers enjoy working in.\nExcited by the challenge of building infrastructure from the ground up rather than inheriting a mature platform.\nNice to have\nPulumi experience\nDagster experience\nAmazon Bedrock\nSageMaker\nOpenSearch\nECS\nPostgreSQL\nRedis\nNew Relic or modern observability platforms\nExperience supporting AI or ML products\nSOC 2 or security/compliance experience\nStartup experience\nWhat this isn't\nThis isn't a traditional DevOps role where tickets get tossed over the wall after development.\nThis isn't an SRE role focused exclusively on uptime.\nThis isn't an ML engineering role building models.\nYou're building the platform that allows all of those disciplines to move faster. You'll own infrastructure decisions, improve how software gets delivered, and help shape the technical foundation of an AI company that's still early enough for your decisions to matter years from now.","description_format":"text","description_chars":6202,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Professional Services","Nonprofits & Foundations"],"lifecycle":[{"event":"open","at":"2026-09-26T08:44:53Z"}],"liveness":{"score":4,"band":"cold","label":"Long shot","p_open":1,"p_active":0.152,"p_room":0.28,"age_days":83,"expected_fill_days":7,"reasons":["conf:3","win:tail","crowd:"],"computed_at":"2026-09-29T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/givzey-ai-platform-engineer","json_url":"https://alion.io/job/givzey-ai-platform-engineer.json","meta":{"generated_at":"2026-09-30T05:41:12Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":4117,"day_limit":5000,"remaining_today":883,"minute_limit":60,"resets_at":"2026-10-01T00:00:00Z"}}}