--- title: 'Senior AI Engineer at Zafran Security' canonical: 'https://feeny.ai/job/senior-ai-engineer-zafran-security-tel-aviv-w3dxa0zjy8yp' type: 'job' last_seen: '2026-11-04' --- # Senior AI Engineer at Zafran Security - **Company:** Zafran Security - **Location:** Tel Aviv, Israel - **Employment:** full-time - **Work type:** onsite - **Posted:** 2026-11-02 - **Last confirmed live:** 2026-11-04 - **Apply:** https://jobs.ashbyhq.com/zafran-security/ff55ae68-4982-4253-89a7-a2f7db407261 ## Job description Zafran is building the next generation of vulnerability and risk management. We bring together complex security data and turn it into clear investigation, prioritization, and action. We're creating a new AI team to build the shared infrastructure, tools, and standards that enable teams across R&D to develop reliable AI-powered capabilities. The team will also own and deliver core AI experiences used across Zafran's platform and organization. About Zafran: Our Mission: To stop the exploitation of vulnerabilities, everywhere. What makes us different: Zafran de-risks 90% of critical vulnerabilities overnight across your hybrid environment, leveraging Agentic Capabilities and your existing security tools to rapidly mitigate and remediate the 10% most likely to be exploited. ​​Who’s behind us: Zafran is backed by Menlo Ventures, Sequoia Capital, Cyberstarts, and a deep belief that cybersecurity should move as fast as attackers do. We’re one of the fastest-growing companies in the industry, scaling to meet demand from the world’s most advanced, security-obsessed organizations. We’re serious about our mission- so expect work that matters, teammates who challenge and inspire you, and plenty of fun along the way! We're looking for a Senior AI Engineer to be one of the team's first engineers and to own Zafran's AI infrastructure end to end — the shared platform every R&D team uses to build, test, ship, and monitor AI features. That platform powers our in-product AI assistant, our background agents, and every AI capability still to come. You'll set the standard for how AI runs in production at Zafran: when a team ships an AI feature, it should be reliable, secure, observable, and cost-efficient by default — because your platform made it that way. What you will do: - Own the AI platform. Design, build, and run the shared agent runtime: model access, tool use, memory and sessions, streaming, and human approval for sensitive actions. - Production-grade. Scaling, fallback between model providers, rate limits, timeouts, and safe rollouts on Kubernetes. - Own evaluation. Build the evaluation framework every team uses to measure quality, correctness, latency, and cost — and catch regressions in CI before customers do. - Own observability and cost. Tracing for every agent run and tool call, token spend per tenant and per feature, and alerts when quality or cost drifts. - Own AI security. Strict tenant isolation, defenses against prompt injection, and guarded data access across a multi-tenant security platform. - Build the tool layer. MCP tools and data connectors that let agents query our security data safely and reliably. - Enable R&D. Shared libraries, templates, and docs so other teams can build, test, deploy, and monitor AI features independently. - Stay hands-on with architecture, implementation, and production issues, and help raise the AI engineering bar across R&D. Requirements: - 5+ years of backend or infrastructure engineering, with strong system design skills. - Proven experience building and operating production-grade AI / LLM infrastructure — real users, real traffic, real incidents. Not prototypes. - Deep hands-on experience with agentic systems: tool use, structured outputs, prompt and context management, retrieval, and long-running or streaming flows. - Experience designing and running LLM evaluations at scale. - Strong Python skills. - Production experience on AWS and Kubernetes, including observability (tracing, metrics, logs). - Ownership mindset — you treat the platform as a product and other engineers as your customers. Experience with the following is a plus: - Experience with Amazon Bedrock, Strands Agents, LiteLLM, MCP, or OpenTelemetry (our current stack). - Experience building internal developer infrastructure used by multiple engineering teams. - Experience with model evaluation, safety controls, governance, or LLM security (guardrails, prompt injection). - Experience operating multi-tenant SaaS systems. - Background in cybersecurity or security-data products. - Familiarity with Go, ElasticSearch, ClickHouse, or Postgres. Why this role matters: AI is a shared capability across Zafran's products and engineering organization. As the owner of the AI infrastructure, you'll build the foundation that lets every R&D team ship AI features faster and more safely — and shape Zafran's AI architecture from the ground up. ## About Zafran Security ## Company Overview - **One-liner**: Zafran Security provides an AI-native Threat Exposure Management platform that unifies vulnerability data, assesses exploitability in context, and automates mitigation and remediation using existing security controls. - **Entity Type**: Private (Series C) - **Headquarters**: New York, New York, United States [linkedin.com] - **Founded**: 2023 (inferred from initial seed funding in early 2024) [linkedin.com] - **Founders**: Sanaz Yashar (CEO) and Ben Seri (CTO) [zafran.io/about] ## Core Business - **Primary industry**: Cybersecurity (vulnerability / exposure management) - **Target customers**: Enterprise security teams (Fortune 500 and high-growth companies) [zafran.io/platform] - **Mission or purpose statement**: “Proactively stop the exploitation of vulnerabilities, everywhere.” [zafran.io/about] ## Products & Services - **Zafran Threat Exposure Management Platform** (SaaS / agentic): End-to-end platform that unifies findings across cloud, on-prem, and AppSec; assesses risk using runtime presence, reachability, exploitability, asset criticality, and existing controls; enables proactive exposure hunting; provides mitigation guidance that leverages compensating controls; and automates remediation via RemOps (generative AI‑powered remediation operations). [zafran.io/platform] - **Zafran Detector** (released Aug 2025): Continuous vulnerability discovery tool that supplements existing scanners. [linkedin.com] - **Agentic Remediation™**: AI agents that research CVE conditions, validate exploitability on live assets, generate remediation scripts, and maintain human oversight with approval workflows. [zafran.io/platform] ## Market Standing - **Valuation/Market Cap**: Not disclosed (private company) - **Key Metric**: Total funding of $105.5M as of December 2025. Breakdown: Seed $5.5M (Mar 2024), Series B $40M (Sep 2024, led by Sequoia Capital and Cyberstarts), Series C $60M (Dec 2025, led by Menlo Ventures). [linkedin.com] - **Notable Investors/Partners**: Sequoia Capital (Doug Leone on board), Cyberstarts (Lior Simon on board), Menlo Ventures (Rama Sekhar on board), Amex Ventures (strategic investor in 2026). Included in Microsoft for Startups Pegasus Program. [zafran.io/about, linkedin.com] - **Growth Signals**: 132 employees (51% YoY growth, +58 people); 30 open positions as of mid‑2026; monthly job postings up 57.9% YoY; expansion across US, Israel, Germany, and UK. [linkedin.com] ## Competitive Advantages - **AI-native, context-aware analysis**: Applies each customer’s unique asset criticality, runtime presence, and existing control stack to determine which vulnerabilities are truly exploitable – eliminating up to 90% of critical false positives. [zafran.io/platform] - **Leverages existing defenses**: Rather than demanding new agents or patch‑only fixes, Zafran maps exposures to compensating controls and provides step‑by‑step mitigation guidance, shrinking exposure windows before patching begins. [zafran.io/platform] - **Closed‑loop automation**: Agentic Remediation and RemOps reduce manual triage, consolidate overlapping CVEs into single remediation actions, and route work automatically via ticketing integrations. [zafran.io/platform] - **Founding team with breach‑response experience**: Co‑founders directly investigated breaches resulting from known vulnerabilities, giving the product a practitioner‑driven design. [zafran.io/about] ## Strategic Focus - **Scale the platform’s adoption among large enterprises** (Fortune 500) and expand the partner ecosystem. - **Continue product innovation** – recent launches include the Zafran Detector and RemOps; ongoing development of agentic capabilities. - **Global talent acquisition** – aggressive hiring across engineering, sales, and customer success to support 50%+ headcount growth. ## Why Work Here - **Culture**: Founded by cybersecurity practitioners who understand the pain of manual vulnerability management. Emphasis on “clarity and speed” and building solutions that make defenders more effective. [zafran.io/about] - **Work model**: Hybrid – offices in New York, Tel Aviv (Israel), and presence in Germany and the UK. Remote options for certain roles (e.g., Channel Manager listed as Remote – CST). [linkedin.com, zafran.io/careers] - **Notable perks / engineering culture**: High ratio of technical staff (40% of known department breakdown); talent drawn from top security companies (Palo Alto Networks, Tenable, Armis, Microsoft). The company values “customer” focus and “building” as core principles. [linkedin.com] - **Growth opportunity**: Joining at a Series C stage with proven product‑market fit and a clear path to scale – an ideal time for impact. ## Sources 1. [zafran.io](https://www.zafran.io/) 2. [zafran.io/about](https://www.zafran.io/about) 3. [zafran.io/platform](https://www.zafran.io/platform) 4. [zafran.io/careers](https://www.zafran.io/careers) 5. 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