AI/ML Engineer

TENEX.AI

AI/ML Engineer at TENEX designing scalable AI systems for cybersecurity. Collaborate with teams to shape AI-driven solutions while leading innovative projects with advanced technologies.

Posted 6/8/2026full-time🇺🇸 United StatesMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

Distributed SystemsDockerGoGRPCJavaKubernetesMicroservicesPythonRust

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

1 - 3+ years of experience in software development, engineering production systems using modern programming languages (Python, Go, Rust, or Java).
Deep knowledge of agentic systems design, such as Centralized and/or Decentralized MAS (Multi-Agent Systems) architectures.
Solid understanding of Graph structures and specifically graph databases.
Hands-on experience building agents, orchestration frameworks (LangChain/LangGraph, Agno AGI, or custom), and evaluation harnesses.
Deep understanding of microservices architecture, containerization (Docker, Kubernetes), and event-driven systems.
Strong fundamentals in API design (REST/gRPC) and distributed systems.
Clear, concise communication skills and a bias for collaborative problem-solving.
Proven track record of gathering consensus and guiding multi-stakeholder initiatives through uncertain boundaries.
Strong problem-solving and analytical skills.

Benefits

Comp & perks

Competitive salary and benefits package
A culture of growth and development, with opportunities to expand your knowledge in AI, cybersecurity, and emerging technologies.

ATS Keywords

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Hard Skills & Tools

PythonGoRustJavaagentic systems designgraph databasesorchestration frameworksmicroservices architecturecontainerizationAPI design

Soft Skills

communication skillscollaborative problem-solvinggathering consensusguiding multi-stakeholder initiativesproblem-solving skillsanalytical skills