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We are seeking an exceptional strategic, execution-driven and success-oriented Head of Corporate Development to scale this function and lead mergers and acquisitions, joint ventures, investments and other short and long-term corporate initiatives. This role reports to our Chief Legal and Corporate Development Officer and works closely with the executive team to identify, evaluate, and execute opportunities that drive sustainable growth and long-term value creation, and also maintains relationships with and ensures satisfaction of our corporate stakeholders. In this role - key to which is enablement - you will be expected to make things happen in the most professional, creative and seamless manner, to turn corporate strategy into business reality.
Responsibilities
Define and execute corporate development strategy aligned with company goals; establish best corporate development practices, playbooks and repeatable processes; develop M&A models, investment theses and advisory board build-up strategy
Monitor market trends, competitive landscape, and emerging opportunities; build and maintain a pipeline of potential M&A and investment targets; identify and evaluate specific M&A and investment opportunities
Lead end-to-end M&A, investment and corporate JV processes, including sourcing, valuation, due diligence, structuring, negotiation and closing; support post-transaction integration planning and execution; coordinate internal stakeholders and external advisors; manage transaction risks, timelines, and approvals
Present strategic recommendations and transaction updates to executive leadership and the board; develop management and board-level materials
Ensure company preparedness for periodic financing; enable an effective, timely and seamless closing of inbound investments; coordinate internal due diligence; manage timelines, approvals, and post-closing investor onboarding
Manage shareholders relations, including periodic updates and presentations; develop shareholder-level materials.

Required ML Platform Engineering Team Lead - Sovereign AI Engineering
We're building AI that nations own and control, deployed where almost no one else can operate. ingesting and structuring complex data, and driving practical actions that can literally impact the lives of billions of people around the world. This role helps make that real.
The Dream Job
It starts with you - a technical leader driven to build both the ML platform and the engineering team behind it. You care about reliable infrastructure, great developer experience, and growing engineers through real ownership. You'll set the technical direction for our ML platform - training pipelines, model serving, feature stores, experiment tracking, and compute orchestration - shaping how models reach production across cloud and on-prem, including air-gapped deployments. A significant part of the platform supports large language models, with unique challenges across training, evaluation, and inference in mission-critical environments. You stay close enough to the codebase to debug production issues, unblock your engineers, and make sound architecture calls.
If you want to make a meaningful impact, join our mission and lead the team that builds the ML platform driving Sovereign AI products - this role is for you.
Responsibilities
Set technical direction for the ML platform - training pipelines, model serving, feature stores, experiment tracking, and compute orchestration - through RFCs, prototypes, design reviews, and build-vs-buy decisions
Lead and grow a team of ML Engineers - hire, mentor, pair on hard problems, and raise the bar through code and design reviews
Contribute to critical systems, debug production issues, and maintain deep context on the codebase to inform technical decisions
Own operational excellence for model serving - set and enforce SLAs, run capacity planning, and keep compute costs predictable
Establish ML engineering standards - reproducible experiments, automated evals, model packaging, CI/CD for models, and observability
Support the full lifecycle of our models - from training on domain-specific data to low-latency inference powering production systems
Work closely with Data Platform, AI, Data Science, and Product teams - translate business priorities into engineering work and manage cross-team dependencies
Measure and improve developer experience - deploy friction, onboarding time, CI turnaround - as seriously as model performance.

We are looking for a Python Engineer who is passionate about software design, code quality and problem solving. This versatile role involves writing production-grade python code that will integrate with 3rd party devices and services to collect data that will be used by our AI platform.
Responsibilities
Design and deliver production-grade, high-quality and robust code.
Research a wide range of software and network devices to find the best data collection solutions.
Collaborate with customers to resolve issues and expand our collection portfolio.
Prioritize collection capabilities together with our product team based on customers needs and define milestones.
Work effectively within a team, contributing to a collaborative and innovative development environment.

Required Research Infra Engineer
The Dream Job
As a Research Infra Engineer, you will build and operate the shared platforms that power our cyber research: data ingestion, connectivity to internal/external systems, scalable analysis environments, and self-serve tools which allow the team moving faster.
Youll partner closely with CyberAI researchers to translate research needs into reliable, secure, cloud-deployed capabilities used across the group. Your goals are to reduces research-toil, improves reproducibility and code quality, and accelerates the path from prototype to shared capability.
Responsibilities
Design, implement, and iterate on internal platforms that support research workflows (e.g., data ingestion, enrichment, indexing, search, labeling, evaluation harnesses, experiment tooling).
Develop durable pipelines and connectors to bring in and normalize research data sources.
Create reusable libraries, templates, CLIs, and services that enable researchers to run analyses and experiments safely and repeatably.
Own deployments, reliability, observability, access control, and cost/performance of the research stack so its usable by all researchers.
Work closely with CyberAI researchers on the development of next-generation artificial cyber researchers and AI-driven analysis capabilities.

Required Research Scientist - Sovereign AI Research
The Dream Job
Nations are waking up to a hard truth: critical intelligence infrastructure built on hyperscaler black boxes isn't a solution it's a dependency. The Sovereign AI Research Group exists to answer that differently.
We're not fine-tuning what already exists. We're rethinking the models architecture from the ground up modular, composable, and built with compute governance as a first-class design constraint, not an afterthought.
We operate under real-world constraints. The interesting problems live at the intersections of disciplines. That's where we operate.
Responsibilities
Open Research Tracks
We are hiring across the following specializations. We expect depth in at least one area and the intellectual range to collaborate across them.
Computer Vision: object detection, segmentation, multimodal grounding, vision-language models, contrastive and self-supervised representation learning, low-resource and few-shot visual recognition.
NLP / Speech: LLMs, NERs, relation extraction, span-based and generative IE, semantic textual similarity, multilingual and cross-lingual transfer.
Reinforcement Learning: MDPs, POMDPs, model-based and model-free RL, Online Offline methods, reward modeling, sim-to-real transfer, compute-aware planning.
Graph Learning: GNNs, graph clustering, community structure, generative methods, knowledge graph embeddings, dense and sparse semantic retrieval.
Optimization: convex and nonconvex optimization, constrained and Lagrangian methods, combinatorial and integer programming, knowledge distillation (response, feature, and relation-based), test-time optimization, Bayesian optimization, resource-aware inference.
Representation Learning: contrastive learning, self-supervised and unsupervised pre-training, disentangled representations, metric learning and embedding spaces, cross-modal and multimodal alignment, meta learning (hypernetworks), transfer learning and domain adaptation, probing and interpretability of learned representations, world models.
Neurosymbolic AI: neuro-symbolic integration, differentiable theorem proving, inductive logic programming (ILP), probabilistic soft logic (PSL), causal inference and structural causal models (SCMs), programmatic and compositional reasoning
Responsibilities:
Define and execute a research within your track, experiments, quality gates, and upper bounds in rigorous manner.
Collaborate across tracks on system integration and cross-disciplinary research.
Collaborate work with engineering teams until production.
Mentor junior researchers and contribute to a culture of technical excellence.

Required Security Researcher
The Dream Job
We are on an expedition to find you, someone who is passionate about creating intuitive, out-of-this-world security research. You'll help us harness the power of our trillions of security signals to rapidly diagnose and alert the latest attacker behaviors, drive critical context-rich signals, construct new tools and automations to support customers, identify threats, and detect advanced attacker techniques.
Responsibilities
Analyze various network devices, configurations and security products
Implement methods and algorithms to discover network topology, relationships between devices and potential lateral movement paths
Conduct network security assessments to identify weaknesses in customers network infrastructure, and recommend mitigations to monitor and limit unauthorized access
Develop research tools and frameworks to perform automatic analysis of network devices and security products
Research and analyze network-related cybersecurity threats and trends
Work closely with other internal engineering and AI teams to integrate new capabilities into our platform and guide cross-product architectural decisions
Act as a security subject matter expert for multidisciplinary teams.

We are looking for an R&D Group Lead to take ownership of the SaasLab group - leading multiple engineering teams responsible for the core platform services that every product depends on. You will drive the technical vision and execution or architectural transformation while ensuring the reliability and scalability of SaaS foundation.
The position requires a strong architectural mindset, experience leading platform and infrastructure-level work, and the ability to balance long-term technical strategy with continuous delivery of business value.
What youll do
Lead and mentor a group of engineers and team leads across multiple domains (core entities, access & API gateway, billing & integrations), fostering growth in design, architecture, and people leadership
Own the SaaS platform end to end - ensuring high availability, security, and operational excellence of the systems that underpin every product
Drive and execute an architectural transformation: decoupling from legacy data stores, building a resilient domain model, and adopting modern patterns like GraphQL Federation
Work closely with product managers and cross-functional stakeholders, taking accountability for group deliveries and ensuring teams ship on time with excellent quality
Lead technical initiatives, processes, methodologies, and architectural decisions across the group
Drive AI Products development, SDLC and process improvements via cutting edge tools and methodologies
Be a meaningful and major member of AFOS leadership team and influence the units engineering vision, processes, and culture

We are seeking a Senior AI Engineer to join our core product organization, where you will design, build, and scale next-generation AI systems powering real-world cybersecurity use cases across our diverse product portfolio (Posture, Detection, and CTI). This role focuses on developing production-grade systems leveraging LLMs, advanced machine learning, and agent-based architectures.
You will join a team within our Cyber R&D organization-leading the companys core product portfolio- while driving AI innovation and establishing engineering best practices across the domain. The team focuses on building and optimizing large-scale AI systems, including LLM-based solutions and advanced multi-agent workflows, working closely with data scientists and researchers to bring ideas into production.
Responsibilities
Design, build, and own end-to-end AI solutions- from data collection and preprocessing to model training, evaluation, and production deployment.
Optimize systems for performance, scalability, and reliability in production environments.
Collaborate closely with product, design, and engineering teams to identify and deliver AI-driven capabilities that address real customer needs.
Stay up to date with emerging AI/ML technologies, frameworks, and best practices, and apply them where they create real impact.
Work across the stack, contributing to backend systems and data pipelines that support large-scale AI applications.
Troubleshoot and resolve complex system issues, including performance bottlenecks, race conditions, and memory-related challenges.
Approach problems with a strong analytical mindset, delivering robust solutions while contributing to a high-performing, collaborative team environment.