Team8 Cyber Stealth Startup- AI / Data Engineer at Team8

Tel Aviv, Tel-Aviv District, Israel -

Full Time

Start Date

Immediate

Expiry Date

17 Jan, 26

Salary

0.0

Posted On

19 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, SQL, Go, PostgreSQL, BigQuery, Snowflake, Spark, Kafka, LLM Integration, AWS, GCP, Azure, Docker, Kubernetes, Data Processing, Traffic Analysis, Event-Driven Architecture

Industry

Venture Capital and Private Equity Principals

Description

Description Join a stealth-mode AI security startup backed by Team8, where you’ll be part of the founding engineering team building intelligent systems that transform complex data into actionable insights. You’ll design, implement, and optimize the data and AI infrastructure that powers our product -integrating language models and smart components directly into high-performance pipelines. Work in a fast-paced, mission-driven environment, solving challenging problems at the intersection of AI, data, and security. Collaborate with a tight-knit, ambitious team where your impact is immediate, your ideas shape the product, and your work lays the foundation for the company’s AI capabilities. If you’re excited by building systems that think, love working with data and models, and want to shape the future of AI-driven cybersecurity - we’d love to meet you. Responsibilities Design, build, and maintain data and AI pipelines that collect, process, and analyze large-scale traffic and system data. Develop intelligent systems that extract definitions, entities, and insights from complex traffic data. Integrate and operationalize LLMs and smaller AI models within production systems to enhance automation and reasoning. Optimize model performance and inference pipelines for efficiency, latency, and scalability. Design data workflows that ensure quality, consistency, and observability across all stages of the pipeline. Collaborate closely with software engineers to embed AI-driven capabilities into core product features. Research and experiment with emerging AI frameworks, model architectures, and data techniques to improve system intelligence. Requirements Qualifications Experience: 4-6+ years of hands-on experience as a Data Engineer, AI Engineer, or Software Engineer working with AI-driven systems. Programming: Strong proficiency in Python and SQL; experience with Go or other backend languages is a plus. Data Systems: Solid understanding of data processing and storage technologies (e.g., PostgreSQL, BigQuery, Snowflake, Spark, Kafka). AI/LLM Integration: Proven experience integrating or fine-tuning LLMs or smaller models (e.g., open-weight or API-based). Cloud & Infrastructure: Proficiency with cloud environments (AWS/GCP/Azure) and container orchestration tools (Docker, Kubernetes). Scalability & Performance: Experience designing systems that efficiently handle large-scale, real-time data. Problem Solving: Creative thinker who enjoys tackling unstructured problems and translating them into elegant, automated solutions. Mindset: Hands-on, curious, and driven by impact - you love building things that work and learn fast. Nice to Have Familiarity with LLM optimization and serving (e.g., quantization, prompt engineering, API orchestration). Experience working with vector databases and retrieval systems (e.g., FAISS, Weaviate, Pinecone). Understanding of network or security-related data and traffic analysis. Experience designing event-driven or streaming architectures. Background in developing AI-driven automation or reasoning systems. Why You’ll Love It Here You’ll work on real-world AI problems - from extracting meaning out of complex traffic to deploying smart systems in production. You’ll have massive ownership and help define how AI is built, deployed, and scaled across the company. You’ll be part of a world-class founding team in one of the most exciting spaces in cybersecurity and AI. Every day brings new challenges, new technologies, and the chance to build intelligence that matters.

Responsibilities

Design, build, and maintain data and AI pipelines that collect, process, and analyze large-scale traffic and system data. Collaborate closely with software engineers to embed AI-driven capabilities into core product features.