Engineering Lead (GenAI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
TL;DR
Engineering Lead (GenAI): Building a conversational SaaS platform for digital investigations using LLMs, RAG, and agentic workflows with an accent on production stability and scalable architecture. Focus on leading a high-impact R&D team, optimizing GenAI pipelines, and removing execution blockers in a fast-paced environment.
Location: Israel - Petah Tikva
Company
is a global leader in digital investigations, providing AI-powered platforms to public safety organizations and intelligence agencies to accelerate justice.
What you will do
- Lead the day-to-day execution, planning, and prioritization of the GenAI development team.
- Own production stability, including triage, prioritization, and resolution tracking.
- Drive high engineering standards across code quality, testing, and system reliability.
- Stay hands-on with system architecture, specifically regarding GenAI pipelines, RAG, and agentic flows.
- Mentor engineers while maintaining a flat, startup-like culture.
- Collaborate with Product, DevOps, and Customer Success to ensure smooth feature delivery.
Requirements
- 10+ years of software engineering experience with a strong backend or full-stack background.
- 3+ years in a technical leadership, team lead, or hands-on manager role.
- Proven experience delivering production SaaS applications.
- Hands-on experience with GenAI/LLM-based systems, such as RAG or Agentic workflows.
- Strong system design skills for scalable, distributed systems.
- Experience working in cloud environments, preferably GCP.
Nice to have
- Experience with agentic frameworks or multi-step AI workflows.
- Background in fast-scaling startups or innovation teams.
- Experience with data-intensive systems, such as BigQuery.
- Familiarity with DevOps and production environments.
- Experience working in high-trust or sensitive data domains.
Culture & Benefits
- Opportunity to work on a real-world GenAI product with meaningful global impact.
- Role as a player-coach in a small, elite team pushing AI boundaries in production.
- Direct influence on product architecture and engineering culture.
- Balanced environment operating at the intersection of execution and innovation.
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