Mitek Systems

Sales

• Own and deliver quarterly and annual partner-sourced revenue targets.
• Drive pipeline creation, acceleration, and deal closure through strategic partners and alliances.
• Activate and enable partners to consistently generate qualified opportunities and bookings.
• Lead co-sell motions, joint account planning, and deal execution with partners.
• Work directly on high-value, complex, and strategic deals from qualification through close.
• Recruit, onboard, and ramp new partners to expand coverage and increase revenue penetration.
• Build strong executive-level and field relationships across partner organizations.
• Develop and execute partner-led go-to-market strategies, campaigns, and incentives.
• Forecast partner pipeline and revenue accurately and consistently.
• Identify whitespace, new market opportunities, and expansion plays within existing accounts.
• Provide partners with sales enablement, positioning, demos, and use-case guidance for Mitek’s fraud and identity solutions.
• Collaborate cross-functionally with Direct Sales, Marketing, Product, Legal, and Finance to remove friction and close deals.
• Represent Mitek at industry events and partner meetings as a trusted advisor and sales leader.
• Serve as a revenue-focused brand ambassador for Mitek’s identity and fraud portfolio.

Channel Sales Manager

Machine Learning Engineer

• Own and manage the backlog for ML-driven biometric and document verification capabilities.
• Translate fraud, identity, and customer requirements into clear and actionable ML work items.
• Partner closely with ML engineers and data scientists to refine problem statements into feasible deliverables.
• Define acceptance criteria that reflect real world performance, not just offline model metrics.
• Participate actively in model design discussions, prioritization, and tradeoff analysis.
• Support model lifecycle activities including training, evaluation, deployment, and retraining.
• Ensure monitoring, drift detection, and feedback loops are incorporated into delivery plans.
• Partner with agent operations and data teams on labeling strategy and data quality.
• Incorporate fraud patterns and adversarial thinking into backlog prioritization.
• Work closely with engineering, fraud, compliance, legal, and customer teams.

Product Owner – Machine Learning

Product Manager

• Define and maintain the product delivery roadmap and backlog, including working with product leadership to prioritize major client deliverables.
• Analyse customer feedback and performance data to identify opportunities for improvement.
• Define clear and actionable epics, acceptance criteria, and requirements documentation.
• Serve as the primary driver of day-to-day product execution for major platform initiatives, including scrum team management and technology partnership.
• Monitor post-release performance and synthesize data to recommend enhancements and inform future roadmap decisions.
• Manage a large, complex cross-product backlog with competing priorities and high operational load, including alignment across multiple areas, ensuring consistency, clarity, and readiness at scale.
• Anticipate risks and proactively manage dependencies, reducing escalation and disruption of roadmap.
• Ensure platform scalability, reliability, and integration readiness.

Senior Product Owner

• Own and manage the backlog for ML-driven biometric and document verification capabilities.
• Translate fraud, identity, and customer requirements into clear and actionable ML work items.
• Partner closely with ML engineers and data scientists to refine problem statements into feasible deliverables.
• Define acceptance criteria that reflect real world performance, not just offline model metrics.
• Serve as the primary product owner for ML and data science teams.
• Participate actively in model design discussions, prioritization, and tradeoff analysis.
• Challenge scope, timelines, and modeling approaches when misaligned with business or risk objectives.
• Propose alternate ideas across data strategy, modeling approaches, workflow design, or deployment patterns.
• Support model lifecycle activities including training, evaluation, deployment, and retraining.
• Ensure monitoring, drift detection, and feedback loops are incorporated into delivery plans.
• Help define rollout, experimentation, and rollback guardrails.
• Partner with agent operations and data teams on labeling strategy and data quality.
• Help define labeling schemas and workflows to support effective model training.
• Identify risks related to label noise, bias, or insufficient coverage across geographies and document types.
• Incorporate fraud patterns and adversarial thinking into backlog prioritization.
• Ensure features and models are resilient to evolving attack vectors such as spoofs, deepfakes, and injection attacks.
• Support layered and defense in depth approaches rather than single model dependency.
• Work closely with engineering, fraud, compliance, legal, and customer teams.
• Support internal and external conversations where ML behavior or performance needs explanation.
• Translate technical constraints into clear delivery expectations for non technical stakeholders.

Senior Product Owner – Machine Learning

Data Engineer

• Be responsible for designing, developing, and maintaining large-scale data systems that support advanced analytics and business intelligence initiatives across Mitek.
• This role involves building sustainable and scalable data pipelines, processes, and platforms that enable efficient collection, transformation, and analysis of data throughout the organization.
• You’ll have a huge impact on how our business operates through building infrastructure to answer questions with data, using software engineering best practices, data management fundamentals, and recent advances in distributed systems (i.e. MapReduce, noSQL databases).
• You will work closely with Product Management, Data Analytics, Software Development, and business stakeholders to deliver reliable, high-performing data feeds, enterprise-level reports, and data solutions that support both strategic business decisions and offline machine use cases.

Senior Data Engineer – Trust Platform

Full-stack Engineer

• Design, develop, deploy, and maintain production-ready, scalable API services
• Build platform solutions using microservices and containerized architectures
• Write and maintain unit, integration, and performance tests
• Develop and maintain internal and public API documentation
• Collaborate with engineering, product, and operations teams across the full development lifecycle
• Participate in Agile/Scrum ceremonies (stand-ups, planning, refinement, retrospectives)
• Support deployment, monitoring, and operational readiness of services in production

Senior Software Engineer – External Data Integrations

Onboarding Specialist

• Responsible for guiding new customers from contract signing, through onboarding, to a point where they are successfully utilizing Mitek’s products.
• Be the Directly Responsible Individual (DRI) for speed and quality of each customer’s implementation, deployment, and optimization of Mitek products.
• Customer Onboarding Manager is responsible for coordinating various technical, marketing, product, and compliance teams within Mitek to facilitate the Customer’s desired technical and business outcomes.
• Implementing long and short term project plans shared between Mitek and enterprise customers.
• Developing and iterating customer onboarding strategy and methodology for enterprise customers across several verticals with the goal of minimizing onboarding time, and post-launch delays to growth.
• Communicate project status internally and externally, escalate when necessary, and develop risk mitigation strategies for any blockers.
• Properly manage escalations related to issues encountered during implementation and initial customer go live.

Senior Customer Onboarding Manager

• Replacing manual, slow onboarding processes with automated, reliable pipelines using modern CI/CD and cloud technologies.
• Design, build, and deploy production-grade APIs and services within a microservices/serverless architecture.
• Own your code from design to deployment, ensuring scalability, security, and performance at every step.
• Automate testing and delivery through robust unit, integration, and performance tests.
• Document your work clearly for internal stakeholders and external developers consuming our public APIs.
• Work closely with ML Teams and engineering teams to integrate existing ML models and services into the onboarding process, improve release quality through automation and testing, and enable faster, more scalable deployments.
• Collaborate cross-functionally with product managers, researchers, and operations teams to translate ideas into production-ready features.
• Participate in Agile ceremonies (stand-ups, sprint planning, retrospectives) and help drive continuous improvement.