AI and Data Science Team Lead
Confirmed on the employer's own hiring board on Oct 18, 2026. First seen by Alion on Oct 12, 2026.
Description
About AllCloud
AllCloud is a leader in amplifying organizations’ cloud potential through AI. With a track record of hundreds of successful migrations and implementations across AWS and Salesforce, AllCloud has developed strategies and solutions that enable businesses of all sizes to remain at the forefront of innovation.
AllCloud is a leader in AI-led professional and managed services. As an AWS Premier and audited managed services Partner, and Salesforce Consulting partner, AllCloud provides comprehensive AI-led cloud journey support, from initial migration to ongoing management through our Engage Managed Services. Our expertise ensures that clients remain aligned with ecosystem best practices while focusing on their core business growth.
AllCloud serves clients across the globe with offices in EMEA and North America. www.allcloud.io
About the Role
We are seeking a visionary and hands-on AI and Data Science Team Lead to head our advanced analytics and AI engineering group. Over the past 7 years, our data infrastructure and customer needs have evolved from foundational data engineering and cloud migrations to cutting-edge Generative AI and Machine Learning solutions.
You will lead a high-performing team of AI Engineers and Data Scientists, taking ownership of the technical direction, architecture, and deployment of production-grade AI systems on AWS. The ideal candidate combines a solid foundational background in complex data architecture with state-of-the-art expertise in Gen AI, RAG pipelines, graph-based reasoning, and Enterprise MLOps. You will work closely with enterprise customers across various sectors (manufacturing, banking, healthcare, and high-tech) to translate business constraints into scalable architectures and ship systems that deliver measurable business impact.
Responsibilities
- Team Leadership: Recruit, mentor, and manage a team of Data Scientists and AI Engineers, driving engineering excellence, technical direction, and best practices.
- System Architecture & Gen AI: Design and deploy end-to-end AI systems, including large-scale Retrieval-Augmented Generation (RAG) pipelines for technical documentation, Text-to-SQL GenBI agents, and advanced AI document processing systems (OCR, semantic extraction).
- Enterprise MLOps: Design and deliver secure, enterprise-grade MLOps platforms on AWS (including CI/CD pipelines, feature stores, and monitoring) to dramatically reduce model deployment times.
- Advanced Data Modeling: Utilize graph embeddings (e.g., Neo4j) and build graph-based AI agents to uncover hidden behavioral patterns, improving LLM reasoning while optimizing token costs and latency.
- Customer & Stakeholder Collaboration: Work directly with enterprise customers to understand business constraints, define architectural standards, and implement governance guardrails and validation layers for safe enterprise adoption and data protection.
- Hands-On Execution: Operate dynamically in both startup and enterprise contexts, balancing the need to ship value quickly with maintaining strict production rigor.
Requirements
- Experience: 7+ years of proven experience designing, deploying, and managing production-grade Machine Learning and AI systems (with a strong foundation in data engineering and scalable pipelines).
- Leadership: Demonstrated experience leading, managing, and mentoring data science or AI engineering teams.
- Cloud & Infrastructure: Deep architectural expertise in the Amazon Web Services (AWS) ecosystem, with a track record of deploying large-scale solutions. Experience defining architectural standards to achieve milestones like the AWS ML Competency is a significant advantage.
- Gen AI & Search: Extensive hands-on experience with Large Language Models (LLMs), deep learning frameworks, domain-specific prompting, and vector search/Elasticsearch.
- Graph Technologies: Strong background in modeling complex data structures using Graph Databases (e.g., Neo4j) to build scalable pipelines for high-volume data.
- Education: M.S. (or equivalent) in Engineering, Mathematics, Computer Science, or a related quantitative field.
- Communication: Excellent interpersonal skills with the ability to lead customer-facing engagements and translate complex technical concepts into business value.
- Fluent in Hebrew and English
AllCloud is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics, or any other basis forbidden under federal, provincial, or local law.