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About This Role
Date limite pour présenter sa candidature :
10/29/2026
Adresse :
VIRTUAL09 \- HomeRes \- FL
Groupe de famille d'emploi :
Technologie
Be among the first dedicated AI Penetration Testers at BMO and help shape how AI systems are secured, challenged, and trusted at enterprise scale. As part of BMO's Security Testing Team, you'll play a key role in building and advancing our AI Security Testing capability, assessing cutting\-edge AI technologies, large language models (LLMs), AI agents, and GenAI solutions before they are deployed across the organization.
In this highly visible role, you'll partner with cybersecurity leaders, engineers, architects, data scientists, and AI governance teams to identify emerging risks, develop innovative testing methodologies, and influence how AI security practices evolve across the enterprise.
What Makes This Role Unique?
- Build something new: Help create and mature a first\-of\-its\-kind AI Security Testing capability within BMO's Security Testing Team.
- Work with emerging technology: Evaluate LLMs, AI agents, GenAI platforms, and machine learning systems using cutting\-edge adversarial testing techniques.
- Drive enterprise impact: Shape security outcomes for some of the bank's most strategic AI initiatives before they reach production.
- Create the future of AI testing: Design and develop new AI adversarial testing methodologies that become part of BMO's long\-term security testing strategy.
- Expand your expertise: Lead security testing exercises, conduct AI threat research, and simulate emerging attack techniques targeting AI systems.
- Work alongside experts: Collaborate with leading security practitioners, AI engineers, architects, and governance teams to solve complex security challenges.
- Flexible remote work: Work remotely within EST or CST time zones.
This role offers a rare opportunity to help define an emerging cybersecurity discipline while building expertise that is becoming increasingly critical across the industry. You'll have the opportunity to influence how AI is securely adopted at scale within one of North America's leading financial institutions.
If you're passionate about offensive security, AI, and pushing the boundaries of what security testing can accomplish, this is a unique opportunity to help define the future of AI security at BMO.
Work remotely in the USA within EST or CST time zones.
KEY Responsibilities:
- Conduct security assessments of AI systems, LLMs, AI agents, and machine learning applications.
- Perform adversarial testing including prompt injection, jailbreaks, model manipulation, and abuse\-case testing.
- Execute application, API, and cloud security testing supporting AI\-enabled solutions.
- Develop repeatable AI security testing methodologies, tools, and automation.
- Partner with development and engineering teams to validate and remediate findings.
- Produce technical reports and executive summaries communicating risks and recommendations.
- Research emerging AI threats and attack techniques.
- Support red team exercises involving AI\-enabled attack scenarios.
CORE Skills :
- Advanced penetration testing experience across web applications, APIs, and cloud environments.
- Hands\-on experience assessing AI/LLM technologies, AI agents, ML models, or GenAI applications.
- Strong understanding of offensive security methodologies and adversarial attack techniques.
- Experience with Python scripting and security tool development/automation.
- Knowledge of OWASP Top 10, API Security Top 10, and emerging OWASP LLM Security risks.
- Experience performing threat modeling and security assessments.
- Strong understanding of authentication, authorization, identity, and cloud security concepts.
- Ability to clearly document findings and remediation recommendations.
Additional Information:
Provides analysis and reporting services in support of businesses/groups and BMO overall. Builds relationships and liaises with stakeholders to understand problems and opportunities and recommends solutions to enable the organization to meet its goals. Analyzes data and creates documents and plans in service of informing, advising, or updating internal stakeholders. Ensures that requirements map to a real business need, are approved by all relevant stakeholders, and meet essential quality standards. Participates or conducts user acceptance testing to ensure that changes made are in alignment with business requirements. Provides great customer service in support of the information security processes, applications and infrastructure.
- Provides strategic input into business decisions as a trusted advisor.
- Acts as a subject matter expert on relevant regulations and policies.
- Provides specialized analytical support to senior management.
- May network with industry contacts to gain competitive insights and best practices.
- Understands and can explain to others the core processes, risks and mitigation techniques for designated areas.
- Anticipates and reduces complexity for others.
- Develops innovative approaches to resolve problems and significant issues.
- Provides input to the strategic direction of the group.
- Acts as the prime subject matter expert for internal/external stakeholders.
- Ensures alignment between stakeholders.
- Defines business requirements for analytics and reporting to ensure data insights inform business decision making.
- Analyzes trends to proactively prevent problems.
- Presents and communicates at all levels within IT and across business units.
- Prepares and delivers presentations for senior leaders.
- Leads the preparation of end user reference materials and prepares end\-user training materials.
- Develops innovative approaches to resolve problems and significant issues.
- Works with vendors to troubleshoot issues, as required.
- Assesses the quality of reports submitted and provides related coaching and support.
- Looks for coaching opportunities with other team members.
- Troubleshoots information security issues within designated business group.
- Gathers requirements and documents these requirements for use in various audits, reports, \& projects.
- Identifies opportunities to strengthen the capability of the information security organization at BMO, such as: sharing expertise to promote technical development, mentoring employees, building communities of practice and networks across information security and technology.
- Works with internal stakeholders to validate their requirements via techniques such as reviews and walkthroughs.
- Facilitates discussions and follows a structured approach to plan, elicit, analyze, document, communicate and manage requirements.
- Analyzes data and information to provide insights and recommendations.
- Collects, organizes, analyzes and disseminates significant amounts of information with attention to detail and accuracy.
- Develops and implements data collection systems and other strategies that optimize statistical efficiency and data quality.
- Identifies, analyzes, and interprets trends or patterns in complex data sets.
- Provides analytical support and insights.
- Filters and "cleans" data, and reviews reports and key performance indicators to locate and correct data issues.
- Performs documentation writing and maintenance of new and existing processes, procedures and requirements.
- Recommends approaches to streamline and integrate information security processes in the organization to improve overall efficiency.
- Remains alert to new information security technologies and threats that present risk to the enterprise and determines the best approach to mitigate these risks.
- Stays abreast of industry trends/risks related to information security, technology and business trends / risks through participation in professional associations, practice communities \& individual learning.
- Ensures consistent, high quality practices/work and the achievement of business results in alignment with business/group strategies and with productivity goals.
- Operates at a group/enterprise\-wide level and serves as a specialist resource to senior leaders and stakeholders.
- Applies expertise and thinks creatively to address unique or ambiguous situations and to find solutions to problems that can be complex and non\-routine.
- Implements changes in response to shifting trends.
- Broader work or accountabilities may be assigned as needed.
- Take measured risks while protecting the bank by applying our Risk Management Framework in the execution of your role, in line with our Risk Culture and within our approved Risk Appetite, making sound and risk informed decisions that align to business strategy, protect assets, and adhere to applicable policy documents (Frameworks, Policies, Standards, Procedures and Supporting documents), laws and regulations.
Qualifications:
- Typically 7\+ years of relevant experience and a post\-secondary degree in Information Security, Computer Science, Engineering, Information Systems, Business or in a related field of study or an equivalent combination of education and experience.
- Multiple Information Security certifications from a well\-recognized institution (e.g. (ISC)2, ISACA, SANS).
- Expert in information security, technology, business requirements gathering and reporting in a financial services setting.
- Data manipulation and analysis skills with the ability to collect, organize, analyze and disseminate significant amounts of information with attention to detail and accuracy \- Expert.
- Knowledge of Information Security processes, procedures and controls \- Expert.
- Understanding and problem solving ability of Information Security issues across the bank \- Expert.
- Understanding of industry standards and frameworks e.g. NIST Cyber Security Framework (CSF), ISO 27001 and 27002 \- Expert.
- Understanding of Information Security risk and regulatory requirements \- In\-depth.
- Understanding of the scope of complexity that exists in the computing environment and the ways which security platforms impact that environment.
- Seasoned professional with a combination of education, experience and industry knowledge.
- Verbal \& written communication skills \- In\-depth / Expert.
- Analytical and problem solving skills \- In\-depth / Expert.
- Influence skills \- In\-depth / Expert.
- Collaboration \& team skills; with a focus on cross\-group collaboration \- In\-depth / Expert.
- Able to manage ambiguity.
- Data driven decision making \- In\-depth / Expert.
Salaire :
$122,400\.00 \- $228,000\.00
Type de rémunération :
Salaire
Ce qui précède représente la fourchette et le type de rémunération de BMO Groupe financier.
Les salaires varieront en fonction de facteurs comme l’emplacement, les compétences, l’expérience, les études et les qualifications pour le poste et pourront inclure une structure de commissions. Les salaires pour les postes à temps partiel seront calculés au prorata du nombre d’heures travaillées régulièrement. Pour les rôles à commission, le salaire susmentionné représente la cible de BMO Groupe financier pour la première année au poste.
La rémunération totale offerte par BMO variera selon le type de rémunération associé au poste et peut comprendre des primes de rendement, des primes discrétionnaires ainsi que d’autres avantages et récompenses. BMO offre également une assurance santé, le remboursement des frais de scolarité, une assurance accident et une assurance vie, ainsi que des régimes d’épargne\-retraite. Pour en savoir plus sur nos avantages sociaux, consultez le site : https://jobs.bmo.com/ca/fr/R%C3%A9mun%C3%A9ration\-globale
À propos de nous
À BMO, nous sommes animés par une raison d’être commune : Avoir le cran de faire une différence dans la vie, comme en affaires. Cette raison d’être nous invite à entraîner des changements positifs et durables pour nos clients, nos collectivités et nos employés. En travaillant ensemble, en innovant et en repoussant les limites, nous transformons des vies et des entreprises et favorisons la croissance économique partout dans le monde.
En tant que membre de l’équipe de BMO, vous êtes valorisé, respecté et entendu, et vous avez plus de moyens pour progresser et obtenir des résultats. Nous nous efforçons de vous aider à obtenir des résultats dès le premier jour, pour vous\-même et nos clients. Nous vous offrirons les outils et les ressources dont vous avez besoin pour franchir de nouvelles étapes, car vous aidez nos clients à franchir les leurs. Au moyen d’une formation et d’un coaching approfondis, de pair avec le soutien de la direction et des occasions de réseautage, nous vous aiderons à acquérir une expérience enrichissante et à élargir votre groupe de compétences.
Pour en savoir plus, visitez\-nous à l’adresse http://jobs.bmo.com/us/en
BMO est fier d’être un employeur qui favorise l’égalité d’accès à l’emploi. Nous évaluons les demandeurs sans tenir compte de la race, de la religion, de la couleur, de l’origine nationale, du sexe (y compris la grossesse, les naissances ou les problèmes de santé connexes), de l’orientation sexuelle, de l’identité de genre, de l’expression de genre, du statut de transgenre, des stéréotypes sexuels, de l’âge, du statut d’ancien combattant protégé, du statut de personne handicapée ou de toute autre caractéristique légalement protégée. Nous tenons également compte des demandeurs qui ont des antécédents criminels, conformément aux lois fédérales, étatiques et locales applicables.
BMO s’engage à travailler avec les personnes handicapées et à leur offrir des mesures d’adaptation raisonnables. Si vous avez besoin d’une mesure d’adaptation raisonnable en raison d’une invalidité dans le cadre d’une partie du processus d’emploi, veuillez envoyer un courriel à l’adresse [email protected] et nous informer de la nature de votre demande et de vos coordonnées.
Remarque aux recruteurs : BMO n’accepte pas les curriculum vitæ non sollicités provenant de toute source autre que le candidat directement. Tout curriculum vitæ non sollicité envoyé à BMO, directement ou indirectement, sera considéré comme la propriété de BMO. BMO ne paiera aucuns frais pour les placements découlant de la réception d’un curriculum vitæ non sollicité. Une agence de recrutement doit d’abord détenir une entente de service écrite valide et dûment signée avant d’envoyer des curriculum vitæ.
Salary Context
This $122K-$228K range is below the median for AI/ML Engineer roles in our dataset (median: $180K across 1841 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At BMO Financial Group, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $218,750 based on 3,817 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($175K) sits 20% below the category median. Disclosed range: $122K to $228K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
BMO Financial Group AI Hiring
BMO Financial Group has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in FL, US. Compensation range: $228K - $228K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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