AI Resume Builder
JOIN NOW Post Job
Drivenets
AI

Senior AI Engineer

Drivenets · תל אביב -יפו, TA, IL

Actively hiring Posted 8 days ago
Sign up to apply

Responsibilities

  • Design and develop LLM-powered security features and internal AI tools — RAG pipelines, multi-agent workflows, prompt-engineered systems for cybersecurity
  • Architect and operate multi-agent systems in production — orchestration, inter-agent communication, task delegation, failure handling at scale
  • Build agent monitoring and observability pipelines — tracing, drift/failure detection, alerting, reliability SLAs
  • Build and maintain scalable MLOps infrastructure — model serving, eval frameworks, experiment tracking, CI/CD for ML
  • Fine-tune and adapt foundation models on internal datasets (network telemetry, security logs, threat intel)
  • Establish best practices for model observability, safety, and responsible AI deployment
  • Stay current with the LLM/GenAI ecosystem; drive updates to the AI SDLC and AI Research cycle

Basic qualifications

  • 5–8 years SWE (2–3 in AI/ML)
  • Production LLM apps (RAG/agents/tool-use/fine-tuning)
  • Production multi-agent systems
  • Agent observability
  • LangChain/LangGraph/Bedrock AgentCore
  • Strong Python
  • MLOps pipelines
  • Transformers/embeddings/vector DBs
  • Cloud + K8s.

Preferred qualifications

  • Cybersecurity background (significant plus)
  • Networking (SDN/BGP)
  • Model eval (LLM-as-judge/RAGAS)
  • MCP
  • Telecom/enterprise SaaS
  • publications/OSS in GenAI.

Tags & focus areas

Used for matching and alerts on DevFound
Ai Ai Engineer Mlops Generative Ai

Next step

Ready to Join the Team?

Apply once with DevFound. We'll route your profile to Drivenets and keep you informed when matching AI roles go live.

  • Single profile, multiple curated AI opportunities
  • No spam roles — only vetted AI positions
  • You choose which roles to apply to
Sign up to apply

No CV uploads. We never share your profile without your consent.

Common Questions

Frequently asked questions

Quick answers about how DevFound's AI matching, resumes, and referrals work.

DevFound's AI Copilot ingests your profile, goals, and live job data to deliver curated matches in seconds. Every match includes a resume variant, suggested referrals, and interview prep so you can act immediately. The more feedback you provide, the sharper the Copilot becomes.

AI-led job searches shrink the hours spent sifting through boards and formatting resumes. DevFound pairs automation with your personal outreach, so you reserve energy for interviews and negotiation. Traditional networking still matters, but AI gives you a lift before you even send a message.

Modern AI roles expect comfort with production-grade code, data fluency, and practical ML tooling. The strongest candidates pair deep technical chops with storytelling—translating model impact to product, GTM, and exec partners. Continuous learning keeps you ahead as stacks evolve.

DevFound rewards active seekers. Keep your profile fresh, respond to match quality prompts, and enable alerts so you never miss a role. The AI prioritizes companies and teams that align with your feedback, accelerating both introductions and interview invites.

High-density tech hubs continue to host the deepest AI talent pools, yet distributed teams are catching up fast. Use DevFound filters to hone in on onsite, hybrid, or fully remote roles and watch openings expand across time zones.

DevFound aggregates thousands of remote AI openings and flags the nuances—core hours, async culture, and visa needs—up front. The Copilot also recommends how to position your distributed work experience so hiring managers know you can thrive on a remote team.

Still have questions?

Contact Support