AI/ML Engineer II

Tenex.AI Inc

$120K — $150K *
US-AnywhereRemote in United States
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 3-5 years software development experience with modern programming languages (Python, Go, Rust, Java)
  • Deep knowledge of agentic systems design, including Multi-Agent Systems (MAS) architectures
  • Solid understanding of graph structures and graph databases
  • Experience building orchestration frameworks and evaluation harnesses
  • Deep familiarity with microservices architecture and containerization (Docker, Kubernetes)
  • Strong fundamentals in API design (REST/gRPC)

Responsibilities

  • Drive and deliver technical components of complex projects through effective communication and execution
  • Design and build the AI layer for autonomous detection and auto-remediation workflows
  • Develop and productionize large-scale models and feature pipelines processing billions of security events
  • Own evaluation and reliability processes, including prompt libraries and fallback strategies
  • Collaborate with product teams and customer success to enhance ML and rule-based detections
  • Experiment with cutting-edge AI methods to stay ahead of cybersecurity threats

Benefits

  • Work with cutting-edge AI-driven cybersecurity technologies
  • Collaborate with a talented and innovative team
  • A culture of growth and development with learning opportunities
  • Competitive salary and benefits package
Full Job Description
As an AI/ML II Engineer at TENEX, you will be a key technical contributor responsible for designing, developing, and optimizing scalable, high-performance AI systems. You will play a crucial role in implementing our AI-driven cybersecurity solutions while collaborating across engineering teams and contributing to technical innovation. Location: This role will require Monday - Thursday onsite in any of our locations. WFH Friday. Job Responsibilities • Project Execution: Ability to drive and deliver technical components of complex projects. This means communicating effectively to align on requirements, executing on high-quality code, and collaborating with senior engineers and stakeholders throughout the development lifecycle. • AI Layer Engineering: Design & build the AI layer that powers autonomous detection, RAG-backed investigation, and auto-remediation workflows. • Productionize Reasoning Engines: Develop and productionize large-scale LLMs, graph-based reasoning engines, and streaming feature pipelines that operate on billions of security events. • Evaluation & Reliability: Own evaluation & reliability-from prompt libraries and fine-tuning to red-team testing, latency budgets, and fallback strategies. • Cross-Functional Collaboration: Partner tightly with Product, Detection Engineering, and Customer Success to translate real-world attacker behavior into robust ML and rule-based detections. • Push the Frontier: Experiment with retrieval-augmented generation, tool-calling agents, and multi-modal models (text + logs + graphs) to keep defenders decisively ahead. Required Skills & Qualifications Software Engineering & Architecture Expertise • Core Engineering: 3-5 years of experience in software development, engineering production systems using modern programming languages (Python, Go, Rust, or Java). • Agentic Systems: Deep knowledge of agentic systems design, such as Centralized and/or Decentralized MAS (Multi-Agent Systems) architectures. • Graph Architectures: Solid understanding of Graph structures and specifically graph databases. • Orchestration Frameworks: Hands-on experience building agents, orchestration frameworks (LangChain/LangGraph, Agno AGI, or custom), and evaluation harnesses. • Distributed Systems: Deep understanding of microservices architecture, containerization (Docker, Kubernetes), and event-driven systems. • APIs: Strong fundamentals in API design (REST/gRPC) and distributed systems. Soft Skills • Communication: Clear, concise communication skills and a bias for collaborative problem-solving. • Leadership Alignment: Proven track record of gathering consensus and guiding multi-stakeholder initiatives through uncertain boundaries. • Analytical Rigor: Strong problem-solving and analytical skills. Nice-to-have • Domain Background: Prior work in cybersecurity (SIEM, EDR, SOAR, or MDR). • Startup Mentality: Background driving high-impact engineering initiatives in high-growth startups or enterprise SaaS. • Cloud Infrastructure: Familiarity with cloud infrastructure security (AWS, GCP, or Azure). Education & Certifications • Bachelor's or Master's degree in Computer Science, Engineering, or a related field. • Relevant certifications (AWS/GCP Professional Engineer, Kubernetes, or security-related credentials) are a plus. Why Join Us? • Opportunity to work with cutting-edge AI-driven cybersecurity technologies and Google SecOps solutions. • Collaborate with a talented and innovative team focused on continuously improving security operations. • Competitive salary and benefits package. • A culture of growth and development, with opportunities to expand your knowledge in AI, cybersecurity, and emerging technologies. If you're passionate about combining cybersecurity expertise with artificial intelligence and have experience with advanced multi-agent architectures, we encourage you to apply!

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