Director, Engineering, Proactive Offense
Lead and scale Horizon3.ai's Offensive Engineering organization, overseeing teams responsible for exploit development, offensive content, and attack automation within the NodeZero platform. Set clear technical and product direction for how NodeZero identifies, exploits, and validates vulnerabilities across large, complex environments. Partner with Product, Precision Defense, and Platform teams to define and deliver offensive capabilities that influence the roadmap and enhance customer outcomes. Drive execution from proof-of-concept through production to transform cutting-edge attack research into scalable, productized features. Stay hands-on to guide architectural decisions and evaluate exploit and automation approaches, mentoring technical leads in building resilient, modular systems. Build, mentor, and scale diverse teams of software engineers, exploit developers, and offensive researchers, fostering a culture of collaboration, creativity, and engineering excellence that bridges offensive and product software development. Collaborate across engineering, product, and GTM teams to align offensive innovation with business priorities and ensure delivery of impactful capabilities for customers. This role is central to the mission of delivering continuous, autonomous security testing at scale.
Agentic Solution Engineer
Partner with Account Executives to discover and scope customer challenges, designing high-value technical solutions that showcase the ROI of Netomi’s platform. Architect and build agentic workflows that integrate generative AI with APIs, databases, and enterprise tools to power experiences for customers' end users. Develop custom demonstrations, prototypes, and proofs of concept using the Netomi platform tailored to specific clients' use cases. Design, test, and refine prompts and AI orchestration chains to optimize performance, reasoning, and reliability across varied use cases. Communicate complex technical concepts clearly and persuasively to audiences ranging from C-level executives to hands-on engineers. Collaborate with product and engineering teams, contributing insights from customer engagements to inform roadmap priorities. Document and present solution designs, workflows, and technical configurations for both internal and client-facing reference.
Salesforce Technical Architect
The Salesforce Technical Architect is responsible for designing and delivering scalable, enterprise-grade cloud solutions across the Salesforce ecosystem, including Sales Cloud, Service Cloud, Experience Cloud, Data Cloud, and Agentforce AI agents. The role includes architecting AI-enabled workflows and autonomous agents, designing enterprise data strategies leveraging Salesforce Data Cloud, and defining scalable enterprise integration architectures using MuleSoft or other iPaaS platforms. The architect provides technical leadership for development teams working with Apex, Lightning Web Components, Visualforce, and Salesforce automation frameworks, and may contribute hands-on when necessary. They ensure solutions are high performance, scalable, secure, and capable of handling large data volumes. The role involves partnering with Delivery Managers, consultants, and client stakeholders to translate business requirements into technical architectures, leading design and code reviews, and mentoring developers and consultants. Additionally, the architect evaluates and implements Salesforce AI capabilities, drives innovation initiatives, serves as a technical advisor to clients on architecture and AI adoption, contributes to internal architecture standards and reusable frameworks, and supports presales and solutioning efforts for complex Salesforce engagements.
US Sales and Partnerships Lead, Digital Diagnostics
Lead the team responsible for the AI/ML Stack infrastructure that bridges ML research and production, evolving the stack to meet large scale ML training and inference workload needs. Develop and execute a long-term vision and roadmap for the MLOps team to support ML development and deployment needs across business units, managing short-term deliveries and long-term architectural transformation. Lead and mentor a team of 6-7+ engineers, strategically allocate resources for support and strategic initiatives. Collaborate cross-functionally with leaders in machine learning, data science, product engineering, and infrastructure to identify pain points, address bottlenecks, and facilitate deployment of new solutions. Architect compute and storage pipelines to manage millions of slides and complex artifacts without data fragmentation or latency. Modernize AI product inference stack to support substantial growth in AI runs globally. Work with Site Reliability Engineering to establish comprehensive system observability metrics including compute utilization, network bottlenecks, and cost attribution. Conduct build versus buy assessments and lead stack refresh audits to benchmark proprietary tools against commercial and open-source alternatives.
Manager, Attack Engineering
The Manager, Attack Engineering leads and grows a team of Attack Engineers specializing in cloud providers, container orchestration platforms, and AI systems including AWS, Azure, OCI, GCP, and Kubernetes. This role involves setting technical direction, priorities, and quality standards for cloud offensive capabilities, mentoring engineers to enhance offensive rigor, delivery quality, and customer-facing clarity, and driving hiring and organizational scaling as the team expands. The manager owns offensive strategy across multiple cloud and container ecosystems and AI-integrated systems, guiding the development of end-to-end attack methodologies including discovery, exploitation, privilege escalation, lateral movement, impact, and verification, ensuring capabilities are realistic, production-safe, and aligned with modern attacker tradecraft. They partner with Product and Design to translate field insights into roadmaps and product capabilities, create feedback loops between attack findings and platform evolution, define next-generation attack surfaces, oversee customer engagements and technical briefings, clearly articulate exploitability, business impact, and remediation, and contribute to external content like blogs and demos.
Machine Learning Engineer
Design, develop, and deploy end-to-end machine learning pipelines, ensuring efficiency in training, validation, and inference. Implement MLOps best practices, including CI/CD for ML models, model versioning, monitoring, and retraining strategies. Optimize ML models using feature engineering, hyperparameter tuning, and scalable inference techniques. Work with structured and unstructured data, leveraging Pandas, NumPy, and SQL for efficient data manipulation. Apply machine learning design patterns to build modular, reusable, and production-ready models. Collaborate with data engineers to develop high-performance data pipelines for training and inference. Deploy and manage models on cloud platforms (AWS, GCP, Azure) with containerization and orchestration tools like Docker and Kubernetes. Maintain model performance by implementing continuous monitoring, bias detection, and explainability techniques.
Agentic Solution Engineer
The Solution Engineer will partner with Account Executives to discover and scope customer challenges, designing high-value technical solutions that showcase the ROI of Netomi’s platform. They will architect and build agentic workflows that integrate generative AI with APIs, databases, and enterprise tools, develop custom demonstrations, prototypes, and proofs of concept using the Netomi platform tailored to specific client use cases, design, test, and refine prompts and AI orchestration chains to optimize performance, reasoning, and reliability. Additionally, they will communicate complex technical concepts clearly to audiences ranging from C-level executives to engineers, collaborate with product and engineering teams to contribute insights from customer engagements, and document and present solution designs, workflows, and technical configurations for both internal and client-facing reference.
Agentic Senior Solution Engineer
Partner with Account Executives to discover and scope customer challenges, designing high-value technical solutions that showcase the ROI of Netomi’s platform. Architect and build agentic workflows that integrate generative AI with APIs, databases, and enterprise tools to power experiences for customer end users. Develop custom demonstrations, prototypes, and proofs of concept using the Netomi platform tailored to specific client use cases. Design, test, and refine prompts and AI orchestration chains to optimize performance, reasoning, and reliability across varied use cases. Communicate complex technical concepts clearly and persuasively to audiences ranging from C-level executives to hands-on engineers. Collaborate with product and engineering teams, contributing insights from customer engagements to inform roadmap priorities. Document and present solution designs, workflows, and technical configurations for both internal and client-facing reference.
Applied AI, Technical Lead, Forward Deployed AI Engineer - Montreal
Lead the technical strategy, execution, and delivery of complex AI solutions for enterprise customers by managing project teams of Applied AI Engineers and ensuring the successful deployment of Mistral AI products. Act as the primary technical point of contact for strategic customers throughout the project lifecycle, from pre-sales to post-implementation, collaborating with research, product, and engineering teams. Deliver critical code for complex projects, stay hands-on with coding, reviewing, and optimizing AI solutions. Mentor and guide technical teams, lead technical discussions during pre-sales, design and oversee implementation of complex AI systems including fine-tuning, RAG, agentic workflows, and custom LLM applications aligning with product roadmaps and open-source initiatives. Drive innovation by identifying trends, evaluating new tools and methodologies, and championing best practices in fine-tuning, inference, and deployment. Work closely with product managers, researchers, and engineers to integrate customer feedback into product development.
Enterprise Solutions Engineer
The Solutions Engineer will act as a technical advisor and trusted consultant to enterprise prospects and customers, driving value-based solutioning and integration of the Decagon AI-native platform into complex customer ecosystems. The role requires partnering with Account Executives to discover and qualify solutions that lead to strong return on investment for customers. Responsibilities include creating and architecting generative AI experiences for customers' end users, developing custom demonstrations using the Decagon platform tailored to specific customer needs and value, and communicating complex technical concepts clearly to diverse stakeholders including C-level decision makers, business users, and engineering stakeholders.
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