{"id":462061,"url":"https://alion.io/job/tenex-ai-aiml-engineer","title":"AI/ML Engineer","company":{"id":177900,"name":"TENEX.AI","domain":"tenex.ai","url":"https://alion.io/company/tenex-ai","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":82,"open_postings":42,"ghost_share":0.214,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":70,"computed_at":"2026-10-17T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"junior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":100000,"max_usd":221000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":348},"experience_years_min":1,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agno","optional":false},{"name":"AI Agents","optional":false},{"name":"Docker","optional":false},{"name":"Fine-tuning","optional":false},{"name":"gRPC","optional":false},{"name":"Java","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM Evaluation","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"Rust","optional":false},{"name":"Tool Use","optional":false},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Edge AI","optional":true},{"name":"GCP","optional":true},{"name":"Google SecOps","optional":true},{"name":"SIEM","optional":true}],"status":"live","first_seen_at":"2026-06-08T19:50:38Z","employer_posted_date":"2026-06-08","last_verified_at":"2026-10-18T11:40:12Z","board_verified":true,"closed_at":null,"days_open":131,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":131},"description":"Company Overview\nTENEX is an AI-native, automation-first, built-for-scale Managed Detection and Response (MDR) provider. We are a force multiplier for defenders, helping organizations enhance their cybersecurity posture through advanced threat detection, rapid response, and continuous protection. Our team is composed of industry experts with deep experience in cybersecurity, automation, and AI-driven solutions. Backed by leading investors, we are rapidly growing and seeking top talent to join our mission of revolutionizing the AI-Native MDR landscape.\nWe’re a fast-growing startup backed by industry experts and top-tier investors led by Crosspoint Capital Partners and also backed by Shield Capital, DTCP (formerly Deutsche Telekom Capital Partners), Deepwork Capital, and the Florida Opportunity Fund. Seed round led by Andreessen Horowitz (a16z). As an early employee, you’ll play a meaningful role in defining and building our culture. Get in on the ground floor. We’re a small but well-funded team that just raised a substantial round - joining now comes with limited risk and unlimited upside.\nAs an AI/ML Engineer at TENEX, you will be a key technical driver responsible for designing, developing, and optimizing scalable, high-performance AI systems. You will play a crucial role in shaping the architecture of our AI-driven cybersecurity solutions while collaborating across engineering teams and driving technical innovation.\nCulture is one of the most important things atTENEX.AI -explore our culture deck atculture.tenex.ai to witness how we embody it, prioritizing the irreplaceable collaboration and community of in-person work.\nLocation: This role will require Monday - Thursday onsite in any of our locations. WFH Friday.\nJob Responsibilities\nProject Execution: Ability to drive and land large abstract projects from start to finish. This means communicating effectively to gather consensus, efficient delegation, and bringing multiple stakeholders on the journey.\n\nAI Layer Engineering: Design & build the AI layer that powers autonomous detection, RAG-backed investigation, and auto-remediation workflows.\n\nProductionize Reasoning Engines: Develop and productionize large-scale LLMs, graph-based reasoning engines, and streaming feature pipelines that operate on billions of security events.\n\nEvaluation & Reliability: Own evaluation & reliability-from prompt libraries and fine-tuning to red-team testing, latency budgets, and fallback strategies.\n\nCross-Functional Collaboration: Partner tightly with Product, Detection Engineering, and Customer Success to translate real-world attacker behavior into robust ML and rule-based detections.\n\nPush the Frontier: Experiment with retrieval-augmented generation, tool-calling agents, and multi-modal models (text + logs + graphs) to keep defenders decisively ahead.\n\nRequired Skills & Qualifications\nSoftware Engineering & Architecture Expertise\nCore Engineering: 1 - 3+ years of experience in software development, engineering production systems using modern programming languages (Python, Go, Rust, or Java).\n\nAgentic Systems: Deep knowledge of agentic systems design, such as Centralized and/or Decentralized MAS (Multi-Agent Systems) architectures.\n\nGraph Architectures: Solid understanding of Graph structures and specifically graph databases.\n\nOrchestration Frameworks: Hands-on experience building agents, orchestration frameworks (LangChain/LangGraph, Agno AGI, or custom), and evaluation harnesses.\n\nDistributed Systems: Deep understanding of microservices architecture, containerization (Docker, Kubernetes), and event-driven systems.\n\nAPIs: Strong fundamentals in API design (REST/gRPC) and distributed systems.\n\nSoft Skills\nCommunication: Clear, concise communication skills and a bias for collaborative problem-solving.\n\nLeadership Alignment: Proven track record of gathering consensus and guiding multi-stakeholder initiatives through uncertain boundaries.\n\nAnalytical Rigor: Strong problem-solving and analytical skills.\n\nNice-to-have\nDomain Background: Prior work in cybersecurity (SIEM, EDR, SOAR, or MDR).\n\nStartup Mentality: Background driving high-impact engineering initiatives in high-growth startups or enterprise SaaS.\n\nCloud Infrastructure: Familiarity with cloud infrastructure security (AWS, GCP, or Azure).\n\nEducation & Certifications\nBachelor’s or Master’s degree in Computer Science, Engineering, or a related field.\n\nRelevant certifications (AWS/GCP Professional Engineer, Kubernetes, or security-related credentials) are a plus.\n\nWhy Join Us?\nOpportunity to work with cutting-edge AI-driven cybersecurity technologies and Google SecOps solutions.\n\nCollaborate with a talented and innovative team focused on continuously improving security operations.\n\nCompetitive salary and benefits package.\n\nA culture of growth and development, with opportunities to expand your knowledge in AI, cybersecurity, and emerging technologies.\n\nIf you're passionate about combining cybersecurity expertise with artificial intelligence and have experience with advanced multi-agent architectures, we encourage you to apply!","description_format":"text","description_chars":5103,"description_truncated":false,"requirements":{"experience_years_min":1,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Information Security","Incident Response","Managed Security","Cybersecurity AI"],"lifecycle":[{"event":"open","at":"2026-09-06T11:22:30Z"}],"visa":[],"liveness":{"score":17,"band":"cold","label":"Long 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