{"id":4334140,"url":"https://alion.io/job/teamstation-ai-delivery-lead","title":"AI Delivery Lead","company":{"id":2889395,"name":"TeamStation","domain":"teamstation.dev","url":"https://alion.io/company/teamstation","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Schema","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_regions","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["AR","BR","CO","MX","AI","AG","AW","BS","BB","BZ","BM","BO","VG","BQ","KY","CL","CR","CU","CW","DM","DO","EC","SV","FK","GF","GD","GP","GT","GY","HT","HN","JM","MQ","MS","NI","PA","PY","PE","PR","KN"],"hiring_countries_total":50,"salary":null,"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"ChatGPT","optional":false},{"name":"Claude","optional":false},{"name":"Confluence","optional":false},{"name":"Cursor","optional":false},{"name":"Jira","optional":false},{"name":"Linear","optional":false},{"name":"Machine Learning","optional":false},{"name":"Miro","optional":false},{"name":"Notion","optional":false},{"name":"RAG","optional":false},{"name":"Scrum","optional":false},{"name":"Slack","optional":false},{"name":"CI/CD","optional":true}],"status":"live","first_seen_at":"2026-05-29T00:00:00Z","employer_posted_date":"2026-11-15","last_verified_at":"2026-11-15T10:08:53Z","board_verified":true,"closed_at":null,"days_open":170,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":170},"description":"At TeamStation AI, we are on a mission to bring together the brightest minds to solve tomorrow’s toughest technology challenges.\nOur work is about more than just AI-it’s about building the future through collaboration and innovation.\nWe believe that the key to solving the world’s most complex problems lies in aligning diverse talents and perspectives. Our AI-powered platform enables cutting-edge scientific and technical teams to work smarter, faster, and together. By joining us, you’ll help unlock new technological breakthroughs and drive innovation where it matters most.\nJoin the Mission at TeamStation AI!\nWhere do we come from?\nWe are seeking visionaries, innovators, and problem solvers who thrive in fast-paced, collaborative environments. If you’re passionate about AI, technology, and solving critical challenges, we want to hear from you. Come be part of a team where your ideas can drive the future.\nLocation: LATAM | Remote\nThis Role Is Not for Most Project Managers\nMost Project Management jobs are professional nagging. You chase people for status updates, move Jira tickets because somebody forgot, sit through meetings that should have been Slack messages, and spend more time managing process than helping teams ship. If your idea of delivery is running ceremonies, updating dashboards, and asking engineers for ETAs, you are going to hate this role.\nWe’re not looking for a project coordinator. We’re not looking for a Scrum Master. We’re not looking for somebody whose entire contribution is asking, “When will this be done?” We’re looking for somebody who can walk into a messy AI environment, figure out what is actually broken, remove friction, make hard calls, and keep teams moving.\nWhat You’re Walking Into\nOur TeamStation AI partner is the global leader in Out of Home (OOH) media technology.\nFor decades, outdoor advertising was largely guesswork. Companies bought billboards, transit placements, and physical advertising inventory with limited visibility into what actually worked. They changed that.\nThey built the technology layer that brings the same level of data science, machine learning, AI, and programmatic decision making used in digital advertising into the physical world. They process massive geospatial datasets, apply deep learning models, and help brands understand real world audience behavior at a scale that was not previously possible.\nThey are effectively building the operating system for physical advertising.\nThe engineering challenges are real. The data is complex. The AI systems are constantly evolving. That’s why this role matters.\nWhat You’ll Own\nDelivery Under Uncertainty\nAI systems are messy. Models change. Data changes. Results change. Priorities change.\nYour job is to keep teams shipping without waiting for perfect information or perfect conditions. You know how to create momentum when uncertainty is part of the environment.\nThreshold Based Decision Making\nAI products do not ship because they are perfect. They ship because risks are understood, managed, and accepted.\nYou will make decisions around:\nWhat ships\nWhat gets delayed\nWhat gets cut\nWhat risks are acceptable\nWhat risks are not\nYou can make decisions when information is incomplete instead of hiding behind endless analysis.\nProtect Engineering Focus\nYour job is to reduce noise, not create more of it.\nYou will:\nControl scope creep\nRemove blockers\nAlign priorities\nManage competing stakeholder demands\nProtect engineering time\nYou understand that every interruption has a cost.\nTranslate AI Complexity into Business Language\nYou can bridge the gap between technical teams and business stakeholders.\nYou understand concepts such as:\nHallucinations\nModel reliability\nInference costs\nLatency\nEvaluation frameworks\nDeployment tradeoffs\nMore importantly, you can explain them in business language without turning every conversation into a machine learning conference.\nImprove Execution Without Bureaucracy\nYou believe in systems. You do not believe in process theater.\nYou create visibility, accountability, and operational clarity without burying teams under layers of unnecessary process.\nReliability Over Demos\nAnyone can build a flashy demo. Production systems are different.\nYou care about:\nReliability\nObservability\nMonitoring\nEvaluation quality\nOperational readiness\nMeasurable business outcomes\nYou prioritize systems that work in production over demos that look good in meetings.\nTools & Environment\nProject & Execution\nJira\nLinear\nNotion\nConfluence\nCommunication\nSlack\nZoom\nCollaboration & Visualization\nMiro\nLucidchart\nTechnical Environment\nYou should be comfortable working around:\nAPIs and integrations\nAI and ML workflows\nData pipelines\nCloud infrastructure\nCI/CD environments\nYou do not need to build these systems yourself, but you need to understand how they work and where they fail.\nThe Non Negotiables\n5+ Years Leading Technical Software Delivery\nYou’ve worked closely with engineering teams and understand how software actually gets delivered under pressure.\nExperience Working in AI/ML or Data Heavy Environments\nYou do not need to be an ML engineer, but you must already understand the operational realities of AI products and data systems.\nYou understand the realities of:\nImperfect models\nHallucinations\nData quality issues\nEvaluation thresholds\nDeployment tradeoffs\nOperational AI constraints\nAI Tooling & Workflow Fluency\nYou actively use AI tools to improve execution, analysis, communication, prioritization, debugging, documentation, or operational workflows. We expect familiarity with modern AI-assisted work environments, not just passive exposure to ChatGPT.\nYou should already be comfortable experimenting with and integrating tools such as:\nChatGPT\nClaude\nGemini\nCursor\nAI copilots\nAI-assisted coding tools\nAI-assisted research tools\nAI workflow automation tools\nThe key is not the tool itself. It’s whether AI has become part of how you operate and solve problems every day.\nAI Operational Thinking\nYou understand concepts like:\nHallucinations\nRAG systems\nEvaluation frameworks\nModel reliability\nPrompt iteration\nDeployment risk\nLatency versus accuracy tradeoffs\nFallback mechanisms\nObservability and monitoring\nYou do not need to be an ML engineer, but these concepts should not be new to you.\nStrong Decision Making Under Ambiguity\nYou can make hard calls when information is incomplete.\nYou do not default to:\n“It depends.”\nYou evaluate risk, make a decision, communicate it clearly, and move forward.\nTechnical Fluency\nYou can comfortably discuss:\nAPIs\nIntegrations\nData pipelines\nDeployments\nCloud environments\nSystem constraints\nReliability tradeoffs\nYou do not need to write production code, but you do need to understand the conversations.\nAgile Without Process Addiction\nYou understand Agile well enough to know where it helps and where it gets in the 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