{"id":58898,"url":"https://alion.io/job/axon-enterprise-ai-infrastructure-engineer","title":"AI Infrastructure Engineer","company":{"id":4101,"name":"Axon Enterprise","domain":"axon.com","url":"https://alion.io/company/axon","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":78,"open_postings":150,"ghost_share":0.007,"stale_share":0.86,"repost_share":0.013,"time_to_fill_p50_days":45,"computed_at":"2026-10-12T06:55:09Z"}},"role":"DevOps","role_family":"DevOps","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Boston, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":154388,"max":247020,"currency":"USD","period":"year","gross":null,"usd_annual":247020},"salary_estimate":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Bicep","optional":false},{"name":"CI/CD","optional":false},{"name":"CloudFormation","optional":false},{"name":"GCP","optional":false},{"name":"GitHub Actions","optional":false},{"name":"JavaScript","optional":false},{"name":"LLM","optional":false},{"name":"Node JS","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Pulumi","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Terraform","optional":false},{"name":"TypeScript","optional":false},{"name":"Vercel","optional":false},{"name":"Confluence","optional":true},{"name":"Jira","optional":true},{"name":"Microsoft Entra ID","optional":true},{"name":"React.js","optional":true},{"name":"ServiceNow","optional":true},{"name":"Slack","optional":true},{"name":"Snowflake","optional":true},{"name":"WhatsApp","optional":true}],"status":"closed","first_seen_at":"2026-08-14T20:25:42Z","employer_posted_date":"2026-09-11","last_verified_at":"2026-09-30T01:10:07Z","board_verified":false,"closed_at":"2026-09-30T01:10:07Z","days_open":46,"trust":{"level":"ok","repost_count":1,"flags":[],"days_open":45},"description":"Join Axon and be a Force for Good.\nAt Axon, we’re on a mission to Protect Life. We’re explorers, pursuing society’s most critical safety and justice issues with our ecosystem of devices and cloud software. Like our products, we work better together. We connect with candor and care, seeking out diverse perspectives from our customers, communities and each other.\nLife at Axon is fast-paced, challenging and meaningful. Here, you’ll take ownership and drive real change. Constantly grow as you work hard for a mission that matters at a company where you matter.\nAI Infrastructure Engineer, Corporate AI Team\nTeam & Role Overview\nAxon’s Corporate AI Team sits within Business Technology and builds internal-facing AI solutions that help employees reduce manual work, move faster, and focus on higher-value work. The team develops AI-powered tools, internal applications, integrations, and automation workflows used across Axon.\nWe’re looking for an AI Infrastructure Engineer to help move internal AI and software prototypes from “it works” to “it is production-ready, secure, reliable, supportable, and maintainable.” This role focuses on the operational backbone of internal applications: infrastructure, CI/CD, deployment patterns, reliability, maintenance, support, and production readiness.\nThis is a hands-on individual contributor role that blends platform engineering, DevOps, internal tools engineering, and applied AI infrastructure. You’ll work closely with Corporate AI, IT, Enterprise Data, Security, and business teams to support applications that replace existing software, augment workflows, and improve how teams operate.\nWe’re open to candidates at multiple levels. This could be a strong platform or DevOps engineer ready to grow into broader ownership, or an experienced infrastructure engineer who has operated internal systems at scale.\nIn this role, you’ll:\nOwn maintenance, support, and operational readiness for internal AI-enabled applications and tools.\n\nHelp productionize prototypes built by Corporate AI, business teams, or technical partners.\n\nImprove infrastructure and deployment patterns, with a focus on Vercel-hosted applications and tools deployed across Azure, AWS, and other environments.\n\nBuild and maintain CI/CD, infrastructure-as-code patterns, monitoring, secrets management, access controls, runbooks, and support processes.\n\nPartner through testing, rollout, UAT, and long-term maintenance so internal tools remain useful, stable, secure, and dependable.\n\nThis is not an AI research role. You do not need to train models or develop novel ML techniques. You should understand how modern AI-powered applications are built, deployed, secured, monitored, and supported in an enterprise environment.\nWhat You’ll Do\nProductionize Internal Tools & Prototypes\nTurn prototypes, proof-of-concepts, and team-built tools into reliable applications for real business users.\n\nImprove production readiness across inherited applications, including deployment configuration, monitoring, error handling, documentation, testing, access controls, and supportability.\n\nPartner with Corporate AI engineers and business teams to move applications from prototype to pilot to production.\n\nSupport UAT and rollout by helping validate that applications meet business needs, are stable for daily use, and have a clear support model.\n\nIdentify reliability, security, scalability, and maintainability gaps before tools become business-critical.\n\nEnsure internal applications are not just built, but owned, supported, and continuously improved.\n\nOwn Infrastructure, CI/CD & Platform Operations\nOwn and improve the operational model for internal applications hosted on Vercel, including deployment patterns, configuration, environment management, access controls, monitoring, and production support.\n\nSupport internal applications running across Azure, AWS, GCP, and other cloud environments, with Azure experience especially helpful.\n\nBuild and maintain CI/CD workflows, primarily using GitHub Actions.\n\nApply infrastructure-as-code concepts using Terraform, Bicep, Pulumi, CloudFormation, or similar tools.\n\nManage platform concerns such as secrets, environment variables, deployment automation, access control, logging, alerting, and operational documentation.\n\nPartner with IT, Security, Enterprise Data, and Corporate AI to align infrastructure patterns with Axon’s security and compliance expectations.\n\nParticipate in shared production support and incident response for internal tools and applications.\n\nMaintain and Improve Existing Systems\nOwn ongoing maintenance and support for internal applications, integrations, web apps, backend services, extensions, and workflow tools.\n\nFix bugs, improve reliability, manage dependency updates, address security patches, and reduce operational toil.\n\nImprove observability so the team can understand application health, usage, errors, cost, and reliability.\n\nCreate runbooks, support documentation, checklists, and escalation paths for applications under Corporate AI ownership.\n\nReduce the burden on engineers focused on net-new work by taking ownership of systems that need upkeep and operational care.\n\nTake pride in brownfield engineering: improving existing systems and making them safer, cleaner, more reliable, and easier to operate.\n\nEstablish Internal Tool Lifecycle Standards\nHelp build a repeatable lifecycle model for internal tools, from prototype intake through production readiness, support, maintenance, and retirement.\n\nCreate practical standards such as production readiness checklists, UAT checklists, CI/CD templates, infrastructure patterns, runbook templates, and support handoff processes.\n\nHelp define what it means for an internal application to be experimental, in pilot, production-ready, business-critical, or ready for deprecation.\n\nImprove how the team inherits, supports, and maintains applications created by other teams or through rapid prototyping.\n\nIdentify opportunities to consolidate, simplify, and standardize internal applications and infrastructure over time.\n\nSupport Applied AI Systems\nSupport infrastructure and operations for AI-powered internal tools, including applications that use LLMs, AI agents, RAG workflows, automation frameworks, and enterprise integrations.\n\nUnderstand core AI application concepts such as prompt engineering, retrieval-augmented generation, agentic workflows, model APIs, evaluations, and AI safety considerations.\n\nHelp ensure AI-enabled tools are deployed with appropriate safeguards around data access, secrets, logging, auditability, and responsible use.\n\nPartner with Corporate AI to ensure AI-powered applications are reliable, secure, supportable, and aligned with Axon’s internal standards.\n\nCollaborate Across Axon\nWork closely with Corporate AI, Enterprise Data, IT, Security, and business stakeholders across Axon.\n\nCommunicate technical risks, tradeoffs, support concerns, and infrastructure needs clearly to technical and non-technical partners.\n\nCollaborate with teams replacing existing software, augmenting workflows, or building internal tools to solve business problems.\n\nSupport internal users and stakeholders during rollout, support, and improvement cycles when needed.\n\nBring ownership to ambiguous problems, especially when applications have unclear support models, incomplete documentation, or evolving requirements.\n\nWhat You Bring\n4+ years of experience in platform engineering, DevOps, infrastructure engineering, internal tools engineering, automation engineering, software engineering, or a related technical role.\n\nStrong cloud infrastructure experience with Azure, AWS, or GCP; Azure experience is especially helpful.\n\nExperience with infrastructure-as-code concepts and tools such as Terraform, Bicep, Pulumi, CloudFormation, or similar.\n\nExperience building, maintaining, or supporting CI/CD pipelines, especially with GitHub Actions.\n\nStrong understanding of deployment patterns, environments, secrets management, access controls, monitoring, logging, and production support.\n\nAbility to read, understand, maintain, and improve application code in Python, TypeScript, JavaScript, Node.js, or similar languages.\n\nExperience supporting production or production-like systems, including bug fixes, incident response, dependency updates, documentation, and reliability improvements.\n\nFamiliarity with AI application concepts such as LLM APIs, prompt engineering, RAG, agents, model evaluation, AI security risks, and responsible AI practices.\n\nStrong ownership mindset, including comfort taking over work others started, bringing order to ambiguity, and making systems more reliable over time.\n\nStrong communication skills and ability to work with technical teams, IT partners, security stakeholders, and internal business users.\n\nComfort with brownfield engineering, maintenance, support, and operational excellence.\n\nPractical, service-oriented mindset focused on whether internal tools work well for the people depending on them.\n\nPreferred Experience\nYou do not need all of these, but experience in several areas will help you ramp quickly:\nOperating applications on Vercel, including configuration, deployments, environment variables, access controls, monitoring, and production support.\n\nSupporting internal tools, enterprise applications, workflow automation, or business-critical internal systems.\n\nAzure infrastructure, identity, networking, application hosting, and security patterns.\n\nAuthentication and authorization patterns such as SSO, OAuth/OIDC, Entra ID / Azure AD, RBAC, service principals, and secrets management.\n\nObservability tools, logging platforms, alerting systems, uptime monitoring, incident response, and operational runbooks.\n\nMaintaining applications built with Python, TypeScript, JavaScript, Node.js, React, or similar modern stacks.\n\nBackend services, APIs, integrations, serverless applications, containers, or cloud-hosted web applications.\n\nAI-powered internal tools, LLM applications, RAG workflows, agents, Slackbots, enterprise integrations, or automation platforms.\n\nIntegrating with enterprise systems such as Slack, Jira, Confluence/Quip, Microsoft 365, Salesforce, Snowflake, ServiceNow, or similar.\n\nWorking in regulated, security-sensitive, or compliance-heavy environments.\n\nCreating engineering standards, templates, checklists, lifecycle models, or production readiness frameworks.\n\nParticipating in UAT, release readiness, stakeholder testing, or internal application rollout processes.\n\nMentoring or enabling other engineers through documentation, templates, examples, or operational best practices.\n\nIdeal Candidate Profile\nThe ideal candidate is a platform-minded engineer who enjoys taking useful but unfinished software and making it dependable. You may have a background as a DevOps engineer, platform engineer, infrastructure engineer, internal tools engineer, automation engineer, or software engineer with strong operational instincts.\nYou are not looking only for greenfield feature work. You are energized by making systems stable, maintainable, observable, secure, and easy to support. You are comfortable inheriting prototypes, understanding how they work, identifying what is missing, and building the infrastructure and operational practices needed to make them successful.\nYou are someone who can say, “I’ll own this,” and then bring structure to the application, deployment, support model, documentation, and long-term maintenance plan.\nSuccess in This Role\nIn your first 30 days, you will build context on Axon’s Corporate AI application landscape, understand the current Vercel and cloud footprint, meet key partners across Corporate AI, IT, Enterprise Data, and Security, and identify the highest-priority reliability and maintenance gaps.\nIn your first 90 days, you will begin owning maintenance for a set of internal applications, improve deployment and monitoring patterns for priority tools, support at least one application through testing or rollout, and es...","description_format":"text","description_chars":17942,"description_truncated":true,"requirements":{"experience_years_min":4,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Equity"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Law Enforcement","Document AI","Video Surveillance"],"lifecycle":[{"event":"open","at":"2026-08-14T20:25:42Z"},{"event":"close","at":"2026-08-28T21:38:14Z"},{"event":"reopen","at":"2026-09-08T20:46:25Z"},{"event":"close","at":"2026-09-30T01:10:07Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 153 · green card filings: 20","filings_12m":153,"filings_prev_12m":109,"green_card_filings_12m":20,"median_offered_wage_usd":147876,"route":null,"cap_exempt":false,"checked_at":"2026-10-03T21:08:04+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)","US Department of Labor: PERM disclosure data (green cards)"],"filings_for_role_12m":75}],"liveness":null,"pay":{"stated_usd_annual":247020,"is_top_pay":true},"html_url":"https://alion.io/job/axon-enterprise-ai-infrastructure-engineer","json_url":"https://alion.io/job/axon-enterprise-ai-infrastructure-engineer.json","meta":{"generated_at":"2026-10-13T02:48:07Z","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":4364,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-14T00:00:00Z"}},"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":4101},"rest":"https://alion.io/mcp/rest/get_company?id=4101"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Faxon-enterprise-ai-infrastructure-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%2Faxon-enterprise-ai-infrastructure-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%2Faxon-enterprise-ai-infrastructure-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/axon-enterprise-ai-infrastructure-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Faxon-enterprise-ai-infrastructure-engineer"}]}