Role-AI security research -Sr Program Manager
Work Site: Toronto, Canada – Day 1 Onsite – min 3 days office.
This person should basically manage the team of AI security research engineers.
2 important skills will be Cyber security + AI management.
Skills
- Al
- Java
- Python
- Go
- Node / Node JS
- Product Management
- Project Management
- Docker
- Kubernetes
- Threat Vulnerability
- API
- Cryptography
JD:
Security Technical Program Manager to lead and coordinate cybersecurity research, engineering, product evaluation, and emerging-technology initiatives from research hypothesis through prototype, proof-of-concept, technical evaluation, enterprise recommendation, and operationalization.
This role will work closely with Security Research Engineers, software engineers, cybersecurity teams, architecture teams, technology vendors, startups, and leadership stakeholders to drive programs across AI Security, Agentic AI, Application Security, quantum/post-quantum cryptography (PQC), blockchain, and other emerging cybersecurity technologies.
A key focus of the role will be coordinating the development and evaluation of agentic AI security harnesses and cybersecurity AI capabilities, while also managing structured evaluations of new cybersecurity products, platforms, and startups through technical testing, benchmarking, and due diligence.
The ideal candidate combines the mindset of a technical program leader, cybersecurity practitioner, and emerging-technology evaluator and is comfortable working with highly technical teams to turn new ideas into measurable cybersecurity capabilities and enterprise recommendations.
Responsibility
1. Lead the planning, coordination, and execution of programs to develop agentic AI security harnesses, prototypes, and proof-of-concepts for new cybersecurity capabilities.
- Establish program roadmaps, priorities, milestones, dependencies, deliverables, and success criteria for cybersecurity research and engineering initiatives.
3. Coordinate research and experimentation across AI Security, Agentic AI, Application Security, quantum/PQC, blockchain, and other emerging technologies.
4. Work closely with technical teams developing and integrating AI agents, LLMs, APIs, security tools, automation frameworks, cloud environments, containers, and security test environments.
5.Translate cybersecurity research hypotheses and emerging technology opportunities into structured technical workstreams, experiments, POCs, and evaluation plans.
6. Manage the lifecycle of initiatives from: research → prototype → testing → benchmarking → recommendation → operationalization.
7. Coordinate the development and evaluation of AI Security Harness capabilities, including agentic security workflows and AI-enabled security automation.
- Establish clear technical requirements, evaluation criteria, benchmarks, and success measures for prototypes and emerging cybersecurity capabilities.
9. Lead and coordinate cybersecurity product and startup evaluations through hands-on technical testing performed by engineering and research teams.
10.Establish structured approaches for evaluating cybersecurity products, technologies, and startups based on:
. Security effectiveness
. Technical capability
. Scalability
. Integration complexity
. Architecture
. Operational applicability
. Enterprise applicability
. Coordinate technical due diligence and independent validation of vendor claims and product capabilities.
.Facilitate product demonstrations, technical deep dives, proof-of-concepts, architecture reviews, and evaluation sessions.
. Work with engineering and research teams to identify product limitations, technical risks, security concerns, and integration requirements.
. Drive clear technical recommendations and decision materials based on research, benchmarks, testing, and product evaluations.
. Maintain visibility into cybersecurity products and technologies progressing through research, evaluation, POC, recommendation, and operationalization.
. Coordinate research and engineering initiatives involving AI red teaming, autonomous penetration testing, agent security, and AI-native security tooling.
. Support experimentation with advanced AI and cybersecurity models and their applicability to cybersecurity use cases.
.Identify dependencies, technical blockers, risks, and resource requirements and drive cross-functional resolution.
.Coordinate collaboration across cybersecurity engineering, security research, Application Security, architecture, infrastructure, cloud, and other technical teams.
. Help transition successful research prototypes and cybersecurity capabilities toward operational and enterprise use.
. Establish program metrics that measure prototype progress, technical evaluation results, cybersecurity effectiveness, product evaluation outcomes, and operational readiness.
. Develop and maintain technical program documentation, research summaries, evaluation findings, decisions, risks, and recommendations.
. Prepare and present technical findings, program status, demonstrations, and recommendations to engineering teams, cybersecurity leadership, and other stakeholders.
. Coordinate engagement with cybersecurity vendors, startups, accelerators, venture or investment stakeholders, where appropriate.
. Ensure research findings, prototypes, source code, evaluation artifacts, and technical knowledge are documented and transferred appropriately.
. Promote disciplined experimentation, measurable outcomes, and repeatable evaluation methodologies across cybersecurity research programs.
Qualification
1. Master’s degree in Cybersecurity, Computer Science, Artificial Intelligence, Computer Engineering, or a related technical field; PhD welcomed.
2. Strong technical understanding of software development and modern engineering environments, including Python, Java, Node.js, Go, C/C++, and other modern programming languages.
3. Experience managing or coordinating highly technical programs involving cybersecurity engineering, research, software development, AI, or emerging technologies.
4. Strong understanding of LLMs, AI agents, tool calling, orchestration frameworks, APIs, cloud technologies, containers, and security automation.
- Strong knowledge of cybersecurity domains including:
- Application Security
- AI Security
- Vulnerability Research
- Threat Modeling
- Secure Development
- Network Security
- Infrastructure Security
- Security Architecture
- Demonstrated ability to translate research hypotheses and technical concepts into structured programs, experiments, prototypes, and measurable deliverables.
3. Experience coordinating technical product evaluations, proof-of-concepts, benchmarking, vendor assessments, or technical due diligence.
- Ability to work effectively with deeply technical researchers and engineers and understand technical architecture, software, models, APIs, security tools, and experimental results.
5. Ability to evaluate and communicate technical considerations involving security, scalability, integration complexity, and enterprise applicability.
6. Strong program-management skills across planning, prioritization, milestones, dependencies, risk management, delivery tracking, and stakeholder coordination.
- Strong technical writing, documentation, presentation, and communication skills.
8. Ability to present complex cybersecurity research and technical findings to engineering, security leadership, and investment or innovation stakeholders.
Highly valued experience includes research papers or presentations at recognized cybersecurity, AI, or systems forums; AI red teaming; autonomous penetration testing; agent security; AI-native security tooling; cybersecurity startup, founder, or early-stage product experience; experience presenting or pitching to venture capital, corporate venture teams, accelerators, or investment stakeholders; patents; open-source security projects; vulnerability research; advanced AI frontier models for cybersecurity; or other demonstrated technical innovation.
Cybersecurity certifications such as CISSP, OSCP, CSSLP, CISM or equivalent are also highly valued.
