AI​/ML Engineer II

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.

• 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 product ionize 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.

• 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 (Lang Chain/Lang Graph, 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.

• 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.

• 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).

• 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.

• Opportunity to work with cutting-edge AI-driven cybersecurity technologies and Google Sec Ops 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.