Note: The job is a remote job and is open to candidates in USA. TENEX.AI is an AI-native, automation-first Managed Detection and Response provider, focused on enhancing cybersecurity through advanced threat detection. As an AI/ML Engineer, you will design and optimize scalable AI systems, collaborating across teams to innovate AI-driven cybersecurity solutions.
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
Skills
- 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
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field
- Prior work in cybersecurity (SIEM, EDR, SOAR, or MDR)
- Background driving high-impact engineering initiatives in high-growth startups or enterprise SaaS
- Familiarity with cloud infrastructure security (AWS, GCP, or Azure)
- Relevant certifications (AWS/GCP Professional Engineer, Kubernetes, or security-related credentials)
Benefits
- Competitive salary and benefits package.
- A culture of growth and development, with opportunities to expand your knowledge in AI, cybersecurity, and emerging technologies.
Company Overview