AI/ML Engineer

Company Overview

As 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.

Culture is one of the most important things at TENEX.AI—explore our culture deck at culture.tenex.ai to witness how we embody it, prioritizing the irreplaceable collaboration and community of in-person work.

Location: This role will require Monday - Thursday onsite in any of our locations. WFH Friday.

Job Responsibilities

• Project 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.
• 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: 1 - 3+ 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!