R&D Director, Cellebrite AI Full Time NEW

Cellebrite’s (Nasdaq: CLBT) mission is to enable its global customers to protect and save lives by enhancing digital investigations and intelligence gathering to accelerate justice in communities around the world. Cellebrite’s AI-powered Digital Investigation Platform enables customers to lawfully access, collect, analyze and share digital evidence in legally sanctioned investigations while preserving data privacy. Thousands of public safety organizations, intelligence agencies and businesses rely on Cellebrite’s digital forensic and investigative solutions—available via cloud, on-premises and hybrid deployments—to close cases faster and safeguard communities. To learn more, visit us at www.cellebrite.com, https://investors.cellebrite.com/investors and find us on social media @Cellebrite

Cellebrite is looking for an exceptional R&D Director to lead Cellebrite AI -the group responsible for building the AI foundation, applied AI capabilities, and production-grade agentic experiences that power the next generation of Cellebrite’s investigative products.

Cellebrite AI owns two major domains:

The first is the Cellebrite AI Platform: the shared AI layer that enables product teams across the Cellebrite portfolio to build reliable, scalable, and responsible AI capabilities. This includes inference services, model serving, agentic system building blocks, tools and skills infrastructure, knowledge and memory capabilities, guardrails, evaluation frameworks, MLOps, and AI service operations.

The second is applied AI and AI meta-applications, including Cellebrite AI Chat -an agentic user assistant experience that sits across Cellebrite applications and helps users delegate increasingly complex investigative workflows to AI.

This role leads a multidisciplinary organization of 20+ AI engineers, software engineers, data scientists, DevOps engineers, and data specialists. The Director will be accountable for both the platform and product-facing AI outcomes: turning research and emerging AI capabilities into production systems that are reliable, measurable, compliant, and deeply integrated into Cellebrite’s global product portfolio.

Success in this role means moving Cellebrite AI beyond isolated capabilities into a strategic AI layer across the company: enabling deeper integration and synergy with Cellebrite products, increasing automation of longer-horizon investigative tasks, improving cost and latency at scale, and building the organizational machinery to continuously improve models, agents, evaluations, and production AI services.

This is a role for a leader who combines AI/ML depth, product intuition, platform thinking, and strong organizational leadership. The right candidate has led real production AI/ML systems – not only API integrations or prompt-based prototypes – and knows how to build teams, systems, and processes that allow AI capabilities to improve continuously and safely in the hands of real users.

Responsibilities:

• Lead Cellebrite AI’s R&D organization of 20+ AI engineers, software engineers, data scientists, DevOps engineers, and data specialists.
• Own the engineering execution and technical direction of the Cellebrite AI Platform.
• Own the engineering delivery of strategic applied AI experiences, including Cellebrite AI Chat and other AI applications that operate across Cellebrite’s product portfolio.
• Partner closely with Product, Engineering, Security, Legal, and Compliance stakeholders to shape the AI roadmap and ensure strong alignment with business, customer, and compliance needs.
• Drive production-grade agentic systems capable of handling increasingly complex, longer-horizon investigative tasks with measurable reliability, traceability, cost efficiency, and responsible AI controls.
• Build and operate repeatable ML and AI development processes, including model iteration, evaluation, deployment, monitoring, feedback loops, and continuous improvement.
• Ensure that AI evaluation frameworks are tightly aligned with product requirements, user value, legal standards, evidentiary expectations, and operational risk.
• Oversee AI systems in production, including reliability, observability, cost, latency, scalability, service quality, and incident response.
• Promote responsible AI practices, including privacy, security, auditability, explainability, human oversight, and legal defensibility.
• Drive adoption of advanced AI-assisted engineering practices, including “dark factory” development patterns that augment the team with AI developers, AI interns, coding agents, and automated engineering workflows.
• Keep Cellebrite AI at the frontier of practical AI adoption by identifying, validating, and productizing relevant advances in GenAI, agentic systems, model serving, evaluation, and applied machine learning.

Requirements:

• BSc or MSc in Computer Science, Software Engineering, or a related technical field. Advanced degree preferred, but exceptional practical experience is equally valued.
• 8+ years of experience across software engineering, AI engineering, ML engineering, data science, and related technical domains.
• 5+ years leading managers and multi-team engineering organizations, with proven ability to recruit, coach, and retain senior technical talent.
• Proven experience delivering production AI-enabled SaaS systems in a successful global company.
• Must have led production AI/ML systems beyond API integration or prompt engineering, with deep understanding of the full AI/ML lifecycle: data, training or fine-tuning, evaluation, deployment, inference, monitoring, feedback loops, retraining, and operations.
• Experience building teams, systems, and processes that support continuous ML improvement, repeatable experimentation, scalable evaluation, and reliable production delivery.
• Strong experience with AI platform capabilities such as model serving, inference infrastructure, MLOps, data/feature pipelines, observability, model monitoring, and cost/performance optimization.
• Experience with applied GenAI and agentic systems, including tool use, orchestration, memory, knowledge grounding, guardrails, evaluations, and human-in-the-loop workflows.
• Strong architectural judgment across cloud-native SaaS, distributed systems, data platforms, AI services, and production reliability.
• Strong responsible AI mindset, including security, privacy, legal defensibility, auditability, explainability, and safe deployment of AI in sensitive customer environments.
• Experience building AI capabilities for regulated, security-sensitive, government, law enforcement, intelligence, legal, or enterprise environments-Advantage
• Experience with digital investigations, forensic data, intelligence analysis, evidence management, or complex analytical workflows-Advantage
• Hands-on familiarity with modern LLM application stacks, agent frameworks, RAG systems, vector search, knowledge graphs, model evaluation frameworks, and AI observability tools-Advantage
• Experience leading globally distributed or hybrid teams-Advantage
• Experience introducing AI-assisted development workflows into engineering organizations-Advantage