Why Cast AI?

Cast AI is an automation platform that operates cloud-native and AI infrastructure at scale. By embedding autonomous decision-making directly into Kubernetes and cloud environments, Cast AI continuously optimizes performance, reliability, and efficiency in production.

The old way doesn't work. As Kubernetes and AI environments grow, manual decisions don’t. Cast AI replaces tickets, alerts, and manual tuning with continuous automation that adapts infrastructure as conditions change. Efficiency and cost savings follow naturally from that automation.

Over 2,100 companies already rely on Cast AI, including Akamai, BMW, Cisco, FICO, HuggingFace, NielsenIQ, Swisscom, and TGS.

Global team, diverse perspectives
We're headquartered in Miami, but our impact is international. We take a global and intentional approach to diversity. Today, Cast AI operates across 34 countries spanning Europe, North America, Latin America, and APAC, bringing a wide range of perspectives into how we build and lead. 

Unicorn momentum
In January 2026, we achieved unicorn status with a strategic investment from Pacific Alliance Ventures, the corporate venture arm of Shinsegae Group (a $50+ billion Korean conglomerate). Our valuation now exceeds $1 billion, and we're just getting started.

Join us as we build the future of autonomous infrastructure.

This is a location-specific opportunity. We are currently accepting applications from candidates residing in the following European countries: Bulgaria, Croatia, Estonia, Greece, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Slovenia, and Ukraine.

We are hiring across multiple teams!

As a Senior Software Engineer, you will have the opportunity to work on different key features of our product. We are currently hiring Senior Software Engineers for the following teams:

- Workload Optimization - Automates workload resource management by dynamically adjusting resource allocations, helping developers significantly reduce costs and improve application reliability.

- Karpenter - The Karpenter team powers the integration between Karpenter and Cast AI, bringing enterprise capabilities to the most popular open source Kubernetes autoscaler. We enhance Karpenter with advanced features that improve application reliability and performance while optimizing costs. By joining the team, you’ll bridge open source innovation with enterprise requirements, directly impacting how organizations run Karpenter at scale.

- Reporting - Builds a scalable reporting system that ingests millions of rows per second into our time-series databases, providing insights into cost savings, workload efficiencies, and Cast AI automation impact.

- Pricing - Drives the synchronization of public and customer cloud resources, availability, and dynamic pricing across all major cloud providers. Empowers autoscaling by leveraging discounts, commitments, and cross-cluster tracking to maximize savings. Provides a reliable source of truth for node pricing, resources, components, discounts, and commitments.

- Autoscaler - Automates Kubernetes node autoscaling to optimize clusters, balance workloads, remove underutilized nodes, and dynamically allocate capacity in real-time, thereby reducing cluster costs by half.

- Identity -  Builds and maintains the trust and access foundation for the entire platform, ensuring every user, service, and workload authenticates and interacts securely and seamlessly at scale.

- Billy -  Powers the critical day-2 operations layer of the platform - from billing and audit trails to notifications and feature flags - ensuring the platform runs reliably, transparently, and at scale for every customer, every day.

Here are some of the tools we use daily:

• Programming Languages: Go
• Cloud & Orchestration: Kubernetes, AWS, GCP, Azure
• Databases & Storage: PostgreSQL, Cloud Object Storage
• Messaging & APIs: GCP Pub/Sub, gRPC for internal communication, REST for public APIs
• Observability: Prometheus, Grafana, Loki, Tempo
• CI/CD & GitOps: GitLab CI with ArgoCD.

Requirements:

• Production experience with Go is strongly preferred; candidates without Go should demonstrate strong systems programming skills in a comparable language.
• Deep hands-on experience with cloud platforms (AWS, GCP, or Azure) - including real understanding of how compute, networking, and storage work under the hood.
• Understanding of Kubernetes internals - autoscaling and networking.
• You've personally driven a complex project end-to-end.
• Strong debugging, optimization, and performance-tuning skills - including query profiling, index design, and database performance tuning beyond ORM usage.
• You've run observability tooling (Prometheus, Grafana, OpenTelemetry) in production.
• CI/CD and DevOps practices experience.
• Strong English skills, both verbal and written.
• Startup mindset: adaptable, proactive, and comfortable with ambiguity.

Responsibilities:

• Design and build distributed systems that operate Kubernetes infrastructure autonomously at scale.
• Write production Go services that interact with AWS, GCP, and Azure APIs for real-time cloud resource management.
• Own features end-to-end: from design through implementation, testing, and production rollout (most projects ship in 1-4 weeks).
• Debug complex production issues across cloud providers, Kubernetes clusters, and distributed services.
• Collaborate with product and other engineering teams to solve problems that don't have textbook solutions.
• Work with time-series data, cloud provider APIs, and Kubernetes control plane internals.

What’s in it for you?

• Competitive salary (€6,500 - €9,000 gross, depending on the level of experience)
• Enjoy a flexible, remote-first global environment.
• Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology.
• Equity options.
• Get quick feedback with a fast-paced workflow. Most feature projects are completed in 1 to 4 weeks.
• Spend 10% of your work time on personal projects or self-improvement. 
• Learning budget for professional and personal development - including access to international conferences and courses that elevate your skills.
• Annual hackathon to spark new ideas and strengthen team bonds.
• Team-building budget and company events to connect with your colleagues.
• Equipment budget to ensure you have everything you need.
• Extra days off to help maintain a healthy work-life balance.

Hiring process

• Screening call with Recruiter
• Hiring Manager interview
• Technical interview (system design)
• Live coding
• Culture Check interview with an executive

*As part of our standard hiring process, we would like to inform you that a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr.
*Please note that Cast AI does not provide any form of visa sponsorship/work permit.

#LI-Remote

Step into a pivotal role at the heart of Enterprise Engineering, where strategy meets execution across a fast-scaling, product-led organisation. As a Technical Program Manager in Super, you’ll operate at the center of multiple high-impact initiatives—connecting four engineering tribes and cross-functional guilds to ensure seamless delivery in a year defined by transformation. Working closely with senior leadership and reporting into the CIO’s office, you will drive the day-to-day orchestration of complex programmes, turning ambitious plans into coordinated action. This is an opportunity to shape how a modern, automation-first platform enables growth, innovation, and operational excellence across an entire enterprise.

Step into a pivotal role at the heart of Enterprise Engineering, where strategy meets execution across a fast-scaling, product-led organisation. As a Technical Program Manager in Super, you’ll operate at the center of multiple high-impact initiatives—connecting four engineering tribes and cross-functional guilds to ensure seamless delivery in a year defined by transformation. Working closely with senior leadership and reporting into the CIO’s office, you will drive the day-to-day orchestration of complex programmes, turning ambitious plans into coordinated action. This is an opportunity to shape how a modern, automation-first platform enables growth, innovation, and operational excellence across an entire enterprise.

Step into a pivotal role at the heart of Enterprise Engineering, where strategy meets execution across a fast-scaling, product-led organisation. As a Technical Program Manager in Super, you’ll operate at the center of multiple high-impact initiatives—connecting four engineering tribes and cross-functional guilds to ensure seamless delivery in a year defined by transformation. Working closely with senior leadership and reporting into the CIO’s office, you will drive the day-to-day orchestration of complex programmes, turning ambitious plans into coordinated action. This is an opportunity to shape how a modern, automation-first platform enables growth, innovation, and operational excellence across an entire enterprise.

Step into a pivotal role at the heart of Enterprise Engineering, where strategy meets execution across a fast-scaling, product-led organisation. As a Technical Program Manager in Super, you’ll operate at the center of multiple high-impact initiatives—connecting four engineering tribes and cross-functional guilds to ensure seamless delivery in a year defined by transformation. Working closely with senior leadership and reporting into the CIO’s office, you will drive the day-to-day orchestration of complex programmes, turning ambitious plans into coordinated action. This is an opportunity to shape how a modern, automation-first platform enables growth, innovation, and operational excellence across an entire enterprise.

About the role

To support the scaling momentum we are witnessing, we are hiring multiple Senior Engineering Managers across several teams. This is a unique opportunity to lead high-performing engineering teams, drive technical excellence, and shape impactful products at scale in a fast-moving, collaborative environment.

We’re looking for someone who has:

• Experience in Technical and People leadership
• Strong exposure to hiring engineers and establishing team culture.
• Deep understanding of the software development lifecycle
• Advocate of servant leadership: Takes a hands-on approach to engineering daily basis.
• Experience resolving complex engineering and communication issues
• Great time management, organizational and multitasking skills

Bonus points for:

• Experience of hiring and scaling a distributed team across multiple domains.
• Experience with developing, deploying, and maintaining microservices-oriented applications

What you’ll be doing:

• Hiring  and leading a the team of engineers; reporting directly to you will be engineers (tech leads, software engineers, QAs)
• Ensure growth and development opportunities for all team members which includes employee coaching and mentoring, identifying and removing roadblocks and distractions, running regular 1:1s and feedback sessions with team members, performing performance reviews for the direct reports
• Nurturing a strong relationship with other engineering managers, technical leads and product managers
• Stakeholder coordination: defining priorities, managing expectations, ensuring regular updates and follow-ups regarding the teams’ scope of work
• Supporting engineering department goals by setting team requirements, goals and timelines
• Making relevant technical and business decisions that ensure predictable delivery in terms of timelines, stability, and performance
• Building and maintaining the culture of engineering excellence - we don’t cut corners when it comes to quality and reliability

About the role

To support the scaling momentum we are witnessing, we are hiring multiple Senior Engineering Managers across several teams. This is a unique opportunity to lead high-performing engineering teams, drive technical excellence, and shape impactful products at scale in a fast-moving, collaborative environment.

We’re looking for someone who has:

• Experience in Technical and People leadership
• Strong exposure to hiring engineers and establishing team culture.
• Deep understanding of the software development lifecycle
• Advocate of servant leadership: Takes a hands-on approach to engineering daily basis.
• Experience resolving complex engineering and communication issues
• Great time management, organizational and multitasking skills

Bonus points for:

• Experience of hiring and scaling a distributed team across multiple domains.
• Experience with developing, deploying, and maintaining microservices-oriented applications

What you’ll be doing:

• Hiring  and leading a the team of engineers; reporting directly to you will be engineers (tech leads, software engineers, QAs)
• Ensure growth and development opportunities for all team members which includes employee coaching and mentoring, identifying and removing roadblocks and distractions, running regular 1:1s and feedback sessions with team members, performing performance reviews for the direct reports
• Nurturing a strong relationship with other engineering managers, technical leads and product managers
• Stakeholder coordination: defining priorities, managing expectations, ensuring regular updates and follow-ups regarding the teams’ scope of work
• Supporting engineering department goals by setting team requirements, goals and timelines
• Making relevant technical and business decisions that ensure predictable delivery in terms of timelines, stability, and performance
• Building and maintaining the culture of engineering excellence - we don’t cut corners when it comes to quality and reliability

We are searching for a highly motivated and versatile Workday Administrator to join our HR Technology team. This pivotal role will be the primary technical expert for our Talent Optimisation, Learning modules and Peakon - Employee Voice, ensuring these critical systems run smoothly, are configured optimally, and deliver an exceptional employee experience. The specific blend of responsibilities is flexible and can be adapted based on the candidate's unique technical skills, demonstrated competencies, and previous experience. We encourage candidates with strong core Workday skills and a desire to grow in a specific area to apply. If you thrive on solving problems, improving processes, and empowering employees through intuitive HR technology, we want to hear from you!

What you'll be doing:

Role Overview: architect of the integrated employee growth lifecycle. This role is responsible for the technical design and maintenance of the Workday Talent Management and Peakon Employee Voice ensuring that performance evaluations, succession planning, and compliance training operate as a single, unified ecosystem.

• Talent Optimization & Performance Design
• Business Process (BP) Engineering: design and optimize the end-to-end Performance Review and Multi-Rater BPs. You build the conditional logic that routes evaluations through different approval chains based on org-level or geography.
• Succession & Calibration: build and maintain Succession Pools and Matrix Grids (9-Box). You facilitate the technical execution of Calibration sessions, ensuring data security and auditability of rating changes.
• Development Planning: configure Development Goals so that they link directly to Learning objects, allowing managers to assign specific courses as part of an employee's annual growth plan.
• Advanced Learning Management (LMS)
• Digital Content Strategy: manage the upload, versioning, and lifecycle of SCORM, AICC, and xAPI content. You ensure that the Learning catalog is organized via a strict hierarchy of Topics and Campaigns.
• Compliance Automation: create sophisticated Learning Assignment Rules (Requirement Groups). You build the logic that automatically enrolls employees in mandatory training based on "Hire Date," "Job Profile Change," or "Location."
• External Content Integration: Manage the Cloud Connect for Learning connectors for third-party providers (e.g., LinkedIn Learning), ensuring that external completions are correctly recorded on the Workday Worker Profile.
• Data Governance & Reporting
• Cross-Module Analytics: build custom reports and Discovery Boards that track the "Training ROI"—comparing learning completion rates against performance rating improvements.
• Security & Anonymity: manage Intersection Security Groups to ensure Talent ratings (high-sensitivity) and Learning transcripts (compliance-sensitivity) are only visible to authorized personnel.
• Audit & Health Checks: perform regular "Tenant Health Checks" to ensure no "broken" learning links exist and that talent pools are populated with active employees.
• Unified Talent Optimisation & Learning Architecture
• Skills Cloud Alignment: manage the Workday Skills Cloud as the common language between modules. You ensure that skills identified in a Performance Review (Talent) map directly to the Course Catalog (Learning).
• Career Hub Management: configure the Career Hub to show employees "Suggested Learning" based on their specific career interests and job profile requirements, without relying on AI-automated suggestions.
• Peakon Employee Voice
• Survey architecture: manage end-to-end survey design, including the strategic integration of Custom Questions and localized attributes to ensure insights are relevant without causing "survey fatigue."
• Platform mastery: act as the primary administrator for the Peakon dashboard, configuring complex permissions and navigating both manager and administrator views to ensure seamless data access.
• Benchmarking: maintain a pulse on organizational health by analyzing how company performance aligns with Gaming industry benchmarks provided within the Peakon ecosystem.
• Statistical integrity: apply statistical logic to all datasets—evaluating significance and participation thresholds—to ensure leadership decisions are based on robust, reliable data rather than outliers.
• Deep-Dive segmentation: utilize advanced segmentation skills to slice data by department, tenure, and location, pinpointing specific "pockets" of engagement or friction.
• Trend analysis: distinguish between cyclical fluctuations and systemic cultural shifts by identifying long-term patterns in "growth" and other key engagement drivers.
• Closing the feedback loop: design and oversee the internal communication process, ensuring survey results are transparently shared back with employees to build trust and ensure every voice feels heard.
• Actionable reporting: translate raw data into clear, narrative-driven reports that help stakeholders move from "viewing scores" to "taking action."
• System Support & Enhancement
• Provide functional support for user inquiries and issues related to these modules.
• Participate in the planning, testing, and deployment of Workday bi-annual releases, assessing impact on owned modules.
• Develop and maintain custom reports (RaaS) and calculated fields specific to Talent, Learning and Peakon.
• Maintain comprehensive documentation for configurations, processes, and integrations.

We're looking for someone with:

• 3+ years of hands-on experience as a Workday Administrator or Functional Lead.
• Proven expertise with Talent Optimisation, Learning Management, and Employee Voice - Peakon business process configuration.
• Proficiency in Workday Business Process configuration, security, and reporting (RaaS, Calculated Fields).
• Excellent analytical, problem-solving, and troubleshooting skills.
• Ability to translate business requirements into effective Workday Learning and Listening solutions.
• Strong communication and collaboration skills, with a focus on employee experience.
• Fluency in spoken and written English is required to support global documentation and communication with cross-functional teams.

Bonus points for:

• Workday Pro certification in Workday Learning, Talent Optimisation or Employee Voice Peakon.
• Experience with other Workday modules (Learning, Peakon, Talent Optimisation) and their interdependencies.
• Experience working in a global organization.

• Experience in Technical and People leadership
• Deep understanding of the software development lifecycle
• Proven experience leading cross-functional teams (e.g. engineering, design, product, QA, data)
• Experience resolving complex engineering and communication issues
• Great time management, organizational and multitasking skills

• Experience with developing, deploying, and maintaining  frontend applications or microservices-oriented applications
• Experience in online casino or sports betting products and driving improvements to them

• Leading the team of engineers; reporting directly to you will be engineers (tech leads, software engineers, QAs)
• Ensure growth and development opportunities for all team members which includes employee coaching and mentoring, identifying and removing roadblocks and distractions, running regular 1:1s and feedback sessions with team members, performing performance reviews for the direct reports
• Nurturing a strong relationship with other engineering managers, technical leads and product managers
• Stakeholder coordination: defining priorities, managing expectations, ensuring regular updates and follow-ups regarding the teams’ scope of work
• Supporting engineering department goals by setting team requirements, goals and timelines
• Making relevant technical and business decisions that ensure predictable delivery in terms of timelines, stability, and performance
• Building and maintaining the culture of engineering excellence - we don’t cut corners when it comes to quality and reliability

Overview

As a Staff Data Product Manager for the Analytics Platform, you will own the vision and roadmap for our core data foundation, primarily powered by Snowflake. Your mission is to bridge the "Perception vs. Reality" gap: while our platform is technically robust (with minimal incidents in 2025), users often find data hard to use or unclear.
You will define the "what" and "why" of our platform , ensuring it transitions from a reactive service to a strategic partner that empowers every team at Super to leverage data and AI capabilities at scale.

Key responsibilities

Product strategy & vision

• Own and articulate the product strategy and long-term vision for the Analytics Platform by defining the end-to-end analytical product lifecycle —- from data producer contract management and quality guardrails to downstream data consumers, their access patterns, and measurable value realisation.
• Develop a long-term vision for the Analytics Platform, aligning with broader data-driven objectives.
• Stay ahead of industry trends in cloud warehousing, data modeling, and emerging AI technologies.
• Propose and explore new ways of utilizing Snowflake to leverage AI capabilities and drive business value.

User research & advocacy

• Define and continuously evolve a clear measurement framework for Analytics Platform usability and adoption; use it to enable data-driven decisions with platform leaders and to directly shape roadmap priorities based on measurable impact.
• Deeply investigate actual customer needs, workflows, and pain points to eliminate "blind spots" in platform adoption.
• Address the gap between technical uptime and user perception by ensuring data is intuitive, clear, and reliable.
• Champion a user-centric culture, transforming how technical and business teams interact with our data models.

Roadmap & stakeholder management

• Build and maintain a prioritized product roadmap, balancing operational excellence with strategic initiatives.
• Collaborate with Product, Marketing, and Data Science to ensure Analytics platform is focused on most impactful initiatives across all areas

Strategic integration

• Partner with Product teams to ensure the Analytics Platform is a first-class citizen in the development lifecycle, not an afterthought.
• Partner with the Analytics Platform and Data leadership to transform high-level objectives into vision, direction and roadmap for a scalable, reliable technical platform.

Execution & delivery

• Translate business goals into well-defined problem statements, user stories, and acceptance criteria.
• Manage the development cycle in an Agile environment, providing clarity on priorities and monitoring progress.
• Ensure every initiative has a defined "Problem to Solve" and clear success measurement.

Qualifications

1. Education & experience

• Bachelor’s or Master’s degree in Business, Computer Science, Data Science, or a related field.
• 6–8+ years of product management experience, specifically with data products or analytics platforms.

2. Technical & domain expertise

• Strong familiarity with Analytics databases (e.g Snowflake, BigQuery, Redshift), ETL pipelines, DWH concepts and BI tools.
• Ability to convert complex technical concepts into clear business value.
• Proven track record in leading cross-functional teams

3. Strong differentiators

• Previous experience driving large-scale data product initiatives from ideation to launch
• Experience in entertainment, online gaming, or sports betting industries.

Overview

As a Staff Data Product Manager for the Analytics Platform, you will own the vision and roadmap for our core data foundation, primarily powered by Snowflake. Your mission is to bridge the "Perception vs. Reality" gap: while our platform is technically robust (with minimal incidents in 2025), users often find data hard to use or unclear.
You will define the "what" and "why" of our platform , ensuring it transitions from a reactive service to a strategic partner that empowers every team at Super to leverage data and AI capabilities at scale.

Key responsibilities

Product strategy & vision

• Own and articulate the product strategy and long-term vision for the Analytics Platform by defining the end-to-end analytical product lifecycle —- from data producer contract management and quality guardrails to downstream data consumers, their access patterns, and measurable value realisation.
• Develop a long-term vision for the Analytics Platform, aligning with broader data-driven objectives.
• Stay ahead of industry trends in cloud warehousing, data modeling, and emerging AI technologies.
• Propose and explore new ways of utilizing Snowflake to leverage AI capabilities and drive business value.

User research & advocacy

• Define and continuously evolve a clear measurement framework for Analytics Platform usability and adoption; use it to enable data-driven decisions with platform leaders and to directly shape roadmap priorities based on measurable impact.
• Deeply investigate actual customer needs, workflows, and pain points to eliminate "blind spots" in platform adoption.
• Address the gap between technical uptime and user perception by ensuring data is intuitive, clear, and reliable.
• Champion a user-centric culture, transforming how technical and business teams interact with our data models.

Roadmap & stakeholder management

• Build and maintain a prioritized product roadmap, balancing operational excellence with strategic initiatives.
• Collaborate with Product, Marketing, and Data Science to ensure Analytics platform is focused on most impactful initiatives across all areas

Strategic integration

• Partner with Product teams to ensure the Analytics Platform is a first-class citizen in the development lifecycle, not an afterthought.
• Partner with the Analytics Platform and Data leadership to transform high-level objectives into vision, direction and roadmap for a scalable, reliable technical platform.

Execution & delivery

• Translate business goals into well-defined problem statements, user stories, and acceptance criteria.
• Manage the development cycle in an Agile environment, providing clarity on priorities and monitoring progress.
• Ensure every initiative has a defined "Problem to Solve" and clear success measurement.

Qualifications

1. Education & experience

• Bachelor’s or Master’s degree in Business, Computer Science, Data Science, or a related field.
• 6–8+ years of product management experience, specifically with data products or analytics platforms.

2. Technical & domain expertise

• Strong familiarity with Analytics databases (e.g Snowflake, BigQuery, Redshift), ETL pipelines, DWH concepts and BI tools.
• Ability to convert complex technical concepts into clear business value.
• Proven track record in leading cross-functional teams

3. Strong differentiators

• Previous experience driving large-scale data product initiatives from ideation to launch
• Experience in entertainment, online gaming, or sports betting industries.

Overview

As a Staff Data Product Manager for the Analytics Platform, you will own the vision and roadmap for our core data foundation, primarily powered by Snowflake. Your mission is to bridge the "Perception vs. Reality" gap: while our platform is technically robust (with minimal incidents in 2025), users often find data hard to use or unclear.
You will define the "what" and "why" of our platform , ensuring it transitions from a reactive service to a strategic partner that empowers every team at Super to leverage data and AI capabilities at scale.

Key responsibilities

Product strategy & vision

• Own and articulate the product strategy and long-term vision for the Analytics Platform by defining the end-to-end analytical product lifecycle —- from data producer contract management and quality guardrails to downstream data consumers, their access patterns, and measurable value realisation.
• Develop a long-term vision for the Analytics Platform, aligning with broader data-driven objectives.
• Stay ahead of industry trends in cloud warehousing, data modeling, and emerging AI technologies.
• Propose and explore new ways of utilizing Snowflake to leverage AI capabilities and drive business value.

User research & advocacy

• Define and continuously evolve a clear measurement framework for Analytics Platform usability and adoption; use it to enable data-driven decisions with platform leaders and to directly shape roadmap priorities based on measurable impact.
• Deeply investigate actual customer needs, workflows, and pain points to eliminate "blind spots" in platform adoption.
• Address the gap between technical uptime and user perception by ensuring data is intuitive, clear, and reliable.
• Champion a user-centric culture, transforming how technical and business teams interact with our data models.

Roadmap & stakeholder management

• Build and maintain a prioritized product roadmap, balancing operational excellence with strategic initiatives.
• Collaborate with Product, Marketing, and Data Science to ensure Analytics platform is focused on most impactful initiatives across all areas

Strategic integration

• Partner with Product teams to ensure the Analytics Platform is a first-class citizen in the development lifecycle, not an afterthought.
• Partner with the Analytics Platform and Data leadership to transform high-level objectives into vision, direction and roadmap for a scalable, reliable technical platform.

Execution & delivery

• Translate business goals into well-defined problem statements, user stories, and acceptance criteria.
• Manage the development cycle in an Agile environment, providing clarity on priorities and monitoring progress.
• Ensure every initiative has a defined "Problem to Solve" and clear success measurement.

Qualifications

1. Education & experience

• Bachelor’s or Master’s degree in Business, Computer Science, Data Science, or a related field.
• 6–8+ years of product management experience, specifically with data products or analytics platforms.

2. Technical & domain expertise

• Strong familiarity with Analytics databases (e.g Snowflake, BigQuery, Redshift), ETL pipelines, DWH concepts and BI tools.
• Ability to convert complex technical concepts into clear business value.
• Proven track record in leading cross-functional teams

3. Strong differentiators

• Previous experience driving large-scale data product initiatives from ideation to launch
• Experience in entertainment, online gaming, or sports betting industries.

Overview

As a Staff Data Product Manager for the Analytics Platform, you will own the vision and roadmap for our core data foundation, primarily powered by Snowflake. Your mission is to bridge the "Perception vs. Reality" gap: while our platform is technically robust (with minimal incidents in 2025), users often find data hard to use or unclear.
You will define the "what" and "why" of our platform , ensuring it transitions from a reactive service to a strategic partner that empowers every team at Super to leverage data and AI capabilities at scale.

Key responsibilities

Product strategy & vision

• Own and articulate the product strategy and long-term vision for the Analytics Platform by defining the end-to-end analytical product lifecycle —- from data producer contract management and quality guardrails to downstream data consumers, their access patterns, and measurable value realisation.
• Develop a long-term vision for the Analytics Platform, aligning with broader data-driven objectives.
• Stay ahead of industry trends in cloud warehousing, data modeling, and emerging AI technologies.
• Propose and explore new ways of utilizing Snowflake to leverage AI capabilities and drive business value.

User research & advocacy

• Define and continuously evolve a clear measurement framework for Analytics Platform usability and adoption; use it to enable data-driven decisions with platform leaders and to directly shape roadmap priorities based on measurable impact.
• Deeply investigate actual customer needs, workflows, and pain points to eliminate "blind spots" in platform adoption.
• Address the gap between technical uptime and user perception by ensuring data is intuitive, clear, and reliable.
• Champion a user-centric culture, transforming how technical and business teams interact with our data models.

Roadmap & stakeholder management

• Build and maintain a prioritized product roadmap, balancing operational excellence with strategic initiatives.
• Collaborate with Product, Marketing, and Data Science to ensure Analytics platform is focused on most impactful initiatives across all areas

Strategic integration

• Partner with Product teams to ensure the Analytics Platform is a first-class citizen in the development lifecycle, not an afterthought.
• Partner with the Analytics Platform and Data leadership to transform high-level objectives into vision, direction and roadmap for a scalable, reliable technical platform.

Execution & delivery

• Translate business goals into well-defined problem statements, user stories, and acceptance criteria.
• Manage the development cycle in an Agile environment, providing clarity on priorities and monitoring progress.
• Ensure every initiative has a defined "Problem to Solve" and clear success measurement.

Qualifications

1. Education & experience

• Bachelor’s or Master’s degree in Business, Computer Science, Data Science, or a related field.
• 6–8+ years of product management experience, specifically with data products or analytics platforms.

2. Technical & domain expertise

• Strong familiarity with Analytics databases (e.g Snowflake, BigQuery, Redshift), ETL pipelines, DWH concepts and BI tools.
• Ability to convert complex technical concepts into clear business value.
• Proven track record in leading cross-functional teams

3. Strong differentiators

• Previous experience driving large-scale data product initiatives from ideation to launch
• Experience in entertainment, online gaming, or sports betting industries.

Overview

As a Senior Data Product Manager – Experimentation, you will own the vision, strategy, and roadmap of our internal experimentation platform. Your primary focus will be defining “what” we build and “why”—ensuring our teams have robust, intuitive tools for A/B testing, audience segmentation, feature flag management, and data-driven decision-making. Through close collaboration with Engineering, Data Science, Marketing, and Product teams, you will champion a hypothesis-driven culture, transforming how we learn, iterate, and innovate at scale. Your work will empower every team at SuperBet to rapidly experiment, reduce time-to-insight, and drive measurable business impact.

Key responsibilities

1. Product strategy & vision

• Develop a clear, long-term product vision for the Experimentation Platform, aligning with the broader data-driven objectives.
• Stay attuned to industry best practices, academic research, and emerging technologies to keep our platform at the cutting edge.

2. Defining the “What” and “Why”

• Translate business goals and user requirements into well-defined problem statements, expected business impact, and success metrics.
• Advocate for the importance of hypothesis-driven development, evangelizing experimentation methodologies across the organization.

3. Roadmap & stakeholder management

• Build and maintain a prioritized product roadmap for experimentation, balancing quick wins with strategic, long-term initiatives.
• Collaborate with cross-functional stakeholders (Product, Marketing, Data Science, Engineering) to gather feedback, refine requirements, and drive alignment.

4. Cross-functional collaboration

• Partner closely with the Senior Engineering Manager to transform high-level product objectives into a scalable, reliable, and efficient technical platform.
• Collaborate with Data Scientists and Analysts to define statistical engines, experiment design templates, and consistent KPI frameworks.
• Work with Marketing and Product teams to ensure the experimentation platform meets diverse needs—ranging from audience segmentation to feature flagging and surveys.

5. Execution & delivery

• Clearly communicate product requirements, user stories, and acceptance criteria to engineering teams.
• Manage the development cycle in an Agile environment, providing clarity on priorities and monitoring progress.
• Ensure each initiative launches with a defined Problem to Solve, Business Impact, and Success Measurement, tracking progress to inform continuous improvement.

6. Performance & impact tracking

• Define robust product success metrics (adoption rates, number of experiments run, time-to-insight, etc.) and implement tracking mechanisms.
• Analyze usage data and experiment results to validate assumptions, identify gaps, and inform product enhancements.
• Champion experimentation quality measurements—ensuring teams follow best practices and extract meaningful insights.
• Work with user communities to collect feedback, refine feature requirements, and iterate on platform improvements.

7. Domain expertise & thought leadership

• Serve as the in-house expert on experimentation methodologies, statistical significance, confidence intervals, and advanced testing frameworks.
• Lead initiatives like an Experimentation Embassy, workshops, and knowledge-sharing sessions to promote best practices across the company.

8. Communication & evangelism

• Own the narrative around experimentation—communicating platform updates, success stories, and impact to both technical and non-technical audiences.
• Continuously evangelize the power of a hypothesis-driven, data-informed approach within the organisation, aligning executives and teams on key objectives.

Qualifications

1. Education & experience

• Bachelor’s or Master’s degree in Business, Computer Science, Data Science, Statistics, or a related field (or equivalent practical experience).
• 6–8+ years of product management experience, ideally with a focus on data products, analytics, or experimentation platforms.

2. Technical & domain expertise

• Strong familiarity with A/B testing, multivariate testing, feature flag management, and audience segmentation.
• Understanding of statistical methods (confidence intervals, p-values, hypothesis testing) and ability to collaborate with data scientists on experiment designs.
• Exposure to data infrastructure, ETL pipelines, BI tools, and relevant technologies.

3. Product management skills

• Proven track record in leading cross-functional teams (Engineering, Data Science, UX) using Agile methodologies.
• Ability to convert complex data or statistical concepts into clear business value and actionable product requirements.
• Skilled in developing roadmaps, facilitating stakeholder alignment, and prioritizing high-impact features.

4. Strong differentiators

• Hands-on experience building experimentation platforms, customer segmentation systems, or ML evaluation frameworks.
• Previous work in entertainment, online gaming, or sports betting industries, especially around experimentation and user experience improvements.
• Previous experience driving large-scale data product initiatives, from ideation to launch.

Overview

As a Senior Data Product Manager – Experimentation, you will own the vision, strategy, and roadmap of our internal experimentation platform. Your primary focus will be defining “what” we build and “why”—ensuring our teams have robust, intuitive tools for A/B testing, audience segmentation, feature flag management, and data-driven decision-making. Through close collaboration with Engineering, Data Science, Marketing, and Product teams, you will champion a hypothesis-driven culture, transforming how we learn, iterate, and innovate at scale. Your work will empower every team at SuperBet to rapidly experiment, reduce time-to-insight, and drive measurable business impact.

Key responsibilities

1. Product strategy & vision

• Develop a clear, long-term product vision for the Experimentation Platform, aligning with the broader data-driven objectives.
• Stay attuned to industry best practices, academic research, and emerging technologies to keep our platform at the cutting edge.

2. Defining the “What” and “Why”

• Translate business goals and user requirements into well-defined problem statements, expected business impact, and success metrics.
• Advocate for the importance of hypothesis-driven development, evangelizing experimentation methodologies across the organization.

3. Roadmap & stakeholder management

• Build and maintain a prioritized product roadmap for experimentation, balancing quick wins with strategic, long-term initiatives.
• Collaborate with cross-functional stakeholders (Product, Marketing, Data Science, Engineering) to gather feedback, refine requirements, and drive alignment.

4. Cross-functional collaboration

• Partner closely with the Senior Engineering Manager to transform high-level product objectives into a scalable, reliable, and efficient technical platform.
• Collaborate with Data Scientists and Analysts to define statistical engines, experiment design templates, and consistent KPI frameworks.
• Work with Marketing and Product teams to ensure the experimentation platform meets diverse needs—ranging from audience segmentation to feature flagging and surveys.

5. Execution & delivery

• Clearly communicate product requirements, user stories, and acceptance criteria to engineering teams.
• Manage the development cycle in an Agile environment, providing clarity on priorities and monitoring progress.
• Ensure each initiative launches with a defined Problem to Solve, Business Impact, and Success Measurement, tracking progress to inform continuous improvement.

6. Performance & impact tracking

• Define robust product success metrics (adoption rates, number of experiments run, time-to-insight, etc.) and implement tracking mechanisms.
• Analyze usage data and experiment results to validate assumptions, identify gaps, and inform product enhancements.
• Champion experimentation quality measurements—ensuring teams follow best practices and extract meaningful insights.
• Work with user communities to collect feedback, refine feature requirements, and iterate on platform improvements.

7. Domain expertise & thought leadership

• Serve as the in-house expert on experimentation methodologies, statistical significance, confidence intervals, and advanced testing frameworks.
• Lead initiatives like an Experimentation Embassy, workshops, and knowledge-sharing sessions to promote best practices across the company.

8. Communication & evangelism

• Own the narrative around experimentation—communicating platform updates, success stories, and impact to both technical and non-technical audiences.
• Continuously evangelize the power of a hypothesis-driven, data-informed approach within the organisation, aligning executives and teams on key objectives.

Qualifications

1. Education & experience

• Bachelor’s or Master’s degree in Business, Computer Science, Data Science, Statistics, or a related field (or equivalent practical experience).
• 6–8+ years of product management experience, ideally with a focus on data products, analytics, or experimentation platforms.

2. Technical & domain expertise

• Strong familiarity with A/B testing, multivariate testing, feature flag management, and audience segmentation.
• Understanding of statistical methods (confidence intervals, p-values, hypothesis testing) and ability to collaborate with data scientists on experiment designs.
• Exposure to data infrastructure, ETL pipelines, BI tools, and relevant technologies.

3. Product management skills

• Proven track record in leading cross-functional teams (Engineering, Data Science, UX) using Agile methodologies.
• Ability to convert complex data or statistical concepts into clear business value and actionable product requirements.
• Skilled in developing roadmaps, facilitating stakeholder alignment, and prioritizing high-impact features.

4. Strong differentiators

• Hands-on experience building experimentation platforms, customer segmentation systems, or ML evaluation frameworks.
• Previous work in entertainment, online gaming, or sports betting industries, especially around experimentation and user experience improvements.
• Previous experience driving large-scale data product initiatives, from ideation to launch.

Overview

As a Senior Data Product Manager – Experimentation, you will own the vision, strategy, and roadmap of our internal experimentation platform. Your primary focus will be defining “what” we build and “why”—ensuring our teams have robust, intuitive tools for A/B testing, audience segmentation, feature flag management, and data-driven decision-making. Through close collaboration with Engineering, Data Science, Marketing, and Product teams, you will champion a hypothesis-driven culture, transforming how we learn, iterate, and innovate at scale. Your work will empower every team at SuperBet to rapidly experiment, reduce time-to-insight, and drive measurable business impact.

Key responsibilities

1. Product strategy & vision

• Develop a clear, long-term product vision for the Experimentation Platform, aligning with the broader data-driven objectives.
• Stay attuned to industry best practices, academic research, and emerging technologies to keep our platform at the cutting edge.

2. Defining the “What” and “Why”

• Translate business goals and user requirements into well-defined problem statements, expected business impact, and success metrics.
• Advocate for the importance of hypothesis-driven development, evangelizing experimentation methodologies across the organization.

3. Roadmap & stakeholder management

• Build and maintain a prioritized product roadmap for experimentation, balancing quick wins with strategic, long-term initiatives.
• Collaborate with cross-functional stakeholders (Product, Marketing, Data Science, Engineering) to gather feedback, refine requirements, and drive alignment.

4. Cross-functional collaboration

• Partner closely with the Senior Engineering Manager to transform high-level product objectives into a scalable, reliable, and efficient technical platform.
• Collaborate with Data Scientists and Analysts to define statistical engines, experiment design templates, and consistent KPI frameworks.
• Work with Marketing and Product teams to ensure the experimentation platform meets diverse needs—ranging from audience segmentation to feature flagging and surveys.

5. Execution & delivery

• Clearly communicate product requirements, user stories, and acceptance criteria to engineering teams.
• Manage the development cycle in an Agile environment, providing clarity on priorities and monitoring progress.
• Ensure each initiative launches with a defined Problem to Solve, Business Impact, and Success Measurement, tracking progress to inform continuous improvement.

6. Performance & impact tracking

• Define robust product success metrics (adoption rates, number of experiments run, time-to-insight, etc.) and implement tracking mechanisms.
• Analyze usage data and experiment results to validate assumptions, identify gaps, and inform product enhancements.
• Champion experimentation quality measurements—ensuring teams follow best practices and extract meaningful insights.
• Work with user communities to collect feedback, refine feature requirements, and iterate on platform improvements.

7. Domain expertise & thought leadership

• Serve as the in-house expert on experimentation methodologies, statistical significance, confidence intervals, and advanced testing frameworks.
• Lead initiatives like an Experimentation Embassy, workshops, and knowledge-sharing sessions to promote best practices across the company.

8. Communication & evangelism

• Own the narrative around experimentation—communicating platform updates, success stories, and impact to both technical and non-technical audiences.
• Continuously evangelize the power of a hypothesis-driven, data-informed approach within the organisation, aligning executives and teams on key objectives.

Qualifications

1. Education & experience

• Bachelor’s or Master’s degree in Business, Computer Science, Data Science, Statistics, or a related field (or equivalent practical experience).
• 6–8+ years of product management experience, ideally with a focus on data products, analytics, or experimentation platforms.

2. Technical & domain expertise

• Strong familiarity with A/B testing, multivariate testing, feature flag management, and audience segmentation.
• Understanding of statistical methods (confidence intervals, p-values, hypothesis testing) and ability to collaborate with data scientists on experiment designs.
• Exposure to data infrastructure, ETL pipelines, BI tools, and relevant technologies.

3. Product management skills

• Proven track record in leading cross-functional teams (Engineering, Data Science, UX) using Agile methodologies.
• Ability to convert complex data or statistical concepts into clear business value and actionable product requirements.
• Skilled in developing roadmaps, facilitating stakeholder alignment, and prioritizing high-impact features.

4. Strong differentiators

• Hands-on experience building experimentation platforms, customer segmentation systems, or ML evaluation frameworks.
• Previous work in entertainment, online gaming, or sports betting industries, especially around experimentation and user experience improvements.
• Previous experience driving large-scale data product initiatives, from ideation to launch.

Overview

As a Senior Data Product Manager – Experimentation, you will own the vision, strategy, and roadmap of our internal experimentation platform. Your primary focus will be defining “what” we build and “why”—ensuring our teams have robust, intuitive tools for A/B testing, audience segmentation, feature flag management, and data-driven decision-making. Through close collaboration with Engineering, Data Science, Marketing, and Product teams, you will champion a hypothesis-driven culture, transforming how we learn, iterate, and innovate at scale. Your work will empower every team at SuperBet to rapidly experiment, reduce time-to-insight, and drive measurable business impact.

Key responsibilities

1. Product strategy & vision

• Develop a clear, long-term product vision for the Experimentation Platform, aligning with the broader data-driven objectives.
• Stay attuned to industry best practices, academic research, and emerging technologies to keep our platform at the cutting edge.

2. Defining the “What” and “Why”

• Translate business goals and user requirements into well-defined problem statements, expected business impact, and success metrics.
• Advocate for the importance of hypothesis-driven development, evangelizing experimentation methodologies across the organization.

3. Roadmap & stakeholder management

• Build and maintain a prioritized product roadmap for experimentation, balancing quick wins with strategic, long-term initiatives.
• Collaborate with cross-functional stakeholders (Product, Marketing, Data Science, Engineering) to gather feedback, refine requirements, and drive alignment.

4. Cross-functional collaboration

• Partner closely with the Senior Engineering Manager to transform high-level product objectives into a scalable, reliable, and efficient technical platform.
• Collaborate with Data Scientists and Analysts to define statistical engines, experiment design templates, and consistent KPI frameworks.
• Work with Marketing and Product teams to ensure the experimentation platform meets diverse needs—ranging from audience segmentation to feature flagging and surveys.

5. Execution & delivery

• Clearly communicate product requirements, user stories, and acceptance criteria to engineering teams.
• Manage the development cycle in an Agile environment, providing clarity on priorities and monitoring progress.
• Ensure each initiative launches with a defined Problem to Solve, Business Impact, and Success Measurement, tracking progress to inform continuous improvement.

6. Performance & impact tracking

• Define robust product success metrics (adoption rates, number of experiments run, time-to-insight, etc.) and implement tracking mechanisms.
• Analyze usage data and experiment results to validate assumptions, identify gaps, and inform product enhancements.
• Champion experimentation quality measurements—ensuring teams follow best practices and extract meaningful insights.
• Work with user communities to collect feedback, refine feature requirements, and iterate on platform improvements.

7. Domain expertise & thought leadership

• Serve as the in-house expert on experimentation methodologies, statistical significance, confidence intervals, and advanced testing frameworks.
• Lead initiatives like an Experimentation Embassy, workshops, and knowledge-sharing sessions to promote best practices across the company.

8. Communication & evangelism

• Own the narrative around experimentation—communicating platform updates, success stories, and impact to both technical and non-technical audiences.
• Continuously evangelize the power of a hypothesis-driven, data-informed approach within the organisation, aligning executives and teams on key objectives.

Qualifications

1. Education & experience

• Bachelor’s or Master’s degree in Business, Computer Science, Data Science, Statistics, or a related field (or equivalent practical experience).
• 6–8+ years of product management experience, ideally with a focus on data products, analytics, or experimentation platforms.

2. Technical & domain expertise

• Strong familiarity with A/B testing, multivariate testing, feature flag management, and audience segmentation.
• Understanding of statistical methods (confidence intervals, p-values, hypothesis testing) and ability to collaborate with data scientists on experiment designs.
• Exposure to data infrastructure, ETL pipelines, BI tools, and relevant technologies.

3. Product management skills

• Proven track record in leading cross-functional teams (Engineering, Data Science, UX) using Agile methodologies.
• Ability to convert complex data or statistical concepts into clear business value and actionable product requirements.
• Skilled in developing roadmaps, facilitating stakeholder alignment, and prioritizing high-impact features.

4. Strong differentiators

• Hands-on experience building experimentation platforms, customer segmentation systems, or ML evaluation frameworks.
• Previous work in entertainment, online gaming, or sports betting industries, especially around experimentation and user experience improvements.
• Previous experience driving large-scale data product initiatives, from ideation to launch.

Overview

As a Senior Data Product Manager – Experimentation, you will own the vision, strategy, and roadmap of our internal experimentation platform. Your primary focus will be defining “what” we build and “why”—ensuring our teams have robust, intuitive tools for A/B testing, audience segmentation, feature flag management, and data-driven decision-making. Through close collaboration with Engineering, Data Science, Marketing, and Product teams, you will champion a hypothesis-driven culture, transforming how we learn, iterate, and innovate at scale. Your work will empower every team at SuperBet to rapidly experiment, reduce time-to-insight, and drive measurable business impact.

Key responsibilities

1. Product strategy & vision

• Develop a clear, long-term product vision for the Experimentation Platform, aligning with the broader data-driven objectives.
• Stay attuned to industry best practices, academic research, and emerging technologies to keep our platform at the cutting edge.

2. Defining the “What” and “Why”

• Translate business goals and user requirements into well-defined problem statements, expected business impact, and success metrics.
• Advocate for the importance of hypothesis-driven development, evangelizing experimentation methodologies across the organization.

3. Roadmap & stakeholder management

• Build and maintain a prioritized product roadmap for experimentation, balancing quick wins with strategic, long-term initiatives.
• Collaborate with cross-functional stakeholders (Product, Marketing, Data Science, Engineering) to gather feedback, refine requirements, and drive alignment.

4. Cross-functional collaboration

• Partner closely with the Senior Engineering Manager to transform high-level product objectives into a scalable, reliable, and efficient technical platform.
• Collaborate with Data Scientists and Analysts to define statistical engines, experiment design templates, and consistent KPI frameworks.
• Work with Marketing and Product teams to ensure the experimentation platform meets diverse needs—ranging from audience segmentation to feature flagging and surveys.

5. Execution & delivery

• Clearly communicate product requirements, user stories, and acceptance criteria to engineering teams.
• Manage the development cycle in an Agile environment, providing clarity on priorities and monitoring progress.
• Ensure each initiative launches with a defined Problem to Solve, Business Impact, and Success Measurement, tracking progress to inform continuous improvement.

6. Performance & impact tracking

• Define robust product success metrics (adoption rates, number of experiments run, time-to-insight, etc.) and implement tracking mechanisms.
• Analyze usage data and experiment results to validate assumptions, identify gaps, and inform product enhancements.
• Champion experimentation quality measurements—ensuring teams follow best practices and extract meaningful insights.
• Work with user communities to collect feedback, refine feature requirements, and iterate on platform improvements.

7. Domain expertise & thought leadership

• Serve as the in-house expert on experimentation methodologies, statistical significance, confidence intervals, and advanced testing frameworks.
• Lead initiatives like an Experimentation Embassy, workshops, and knowledge-sharing sessions to promote best practices across the company.

8. Communication & evangelism

• Own the narrative around experimentation—communicating platform updates, success stories, and impact to both technical and non-technical audiences.
• Continuously evangelize the power of a hypothesis-driven, data-informed approach within the organisation, aligning executives and teams on key objectives.

Qualifications

1. Education & experience

• Bachelor’s or Master’s degree in Business, Computer Science, Data Science, Statistics, or a related field (or equivalent practical experience).
• 6–8+ years of product management experience, ideally with a focus on data products, analytics, or experimentation platforms.

2. Technical & domain expertise

• Strong familiarity with A/B testing, multivariate testing, feature flag management, and audience segmentation.
• Understanding of statistical methods (confidence intervals, p-values, hypothesis testing) and ability to collaborate with data scientists on experiment designs.
• Exposure to data infrastructure, ETL pipelines, BI tools, and relevant technologies.

3. Product management skills

• Proven track record in leading cross-functional teams (Engineering, Data Science, UX) using Agile methodologies.
• Ability to convert complex data or statistical concepts into clear business value and actionable product requirements.
• Skilled in developing roadmaps, facilitating stakeholder alignment, and prioritizing high-impact features.

4. Strong differentiators

• Hands-on experience building experimentation platforms, customer segmentation systems, or ML evaluation frameworks.
• Previous work in entertainment, online gaming, or sports betting industries, especially around experimentation and user experience improvements.
• Previous experience driving large-scale data product initiatives, from ideation to launch.

Engineering Manager

This isn't a coordination role. It's a people-first, delivery-accountable, technically credible leadership position at the heart of one of the most genuinely interesting engineering transformations in hospitality tech. You'll lead a team of 5–10 engineers through a live monolith-to-microservices migration, a frontend re-platform, and the shift to AI-first engineering — where 50–70% of code is already AI-generated and the management job has fundamentally changed as a result.

What Makes Us Different?

Duetto is the hospitality industry's leading revenue management platform, founded in 2012 by former Wynn Resorts executives who knew the industry needed better technology. We built the world's first Revenue & Profit Operating System — a suite of tools (GameChanger, ScoreBoard, BlockBuster, Advance and more) that goes beyond room pricing to give hotels, resorts and casinos a complete picture of their revenue and profitability. Trusted by clients ranging from independent boutique hotels to global chains, we've been named the #1 Revenue Management Software by HotelTechAwards four years running and the #1 Best Place to Work in Hotel Tech in 2025. Backed by GrowthCurve Capital since 2024, we're accelerating our investment in AI — and we're genuinely passionate about the industry we serve. We build products we're proud of, for customers we care about.

What You'll Be Doing

• You'll lead the people: running structured weekly 1:1s focused on growth and wellbeing, owning the full performance cycle, building hiring pipelines from scratch, and creating the psychological safety that lets engineers do their best work — including raising problems early and challenging assumptions, including yours.
• You'll own delivery: sprint planning, backlog refinement, roadmap trade-offs with your Product Manager, and the discipline to surface scope and timeline risks before they become surprises — you're a co-owner of the roadmap, not an executor of someone else's plan.
• You'll drive technical health: partnering with your Tech Lead on architectural direction, championing observability, documentation, and quality standards, and ensuring the team balances feature delivery with the technical investment that makes them faster over time.
• You'll lead through transformation: supporting your team through the monolith-to-microservices migration, the BLAST frontend platform shift, and the move to a generate-and-review engineering model — coaching engineers to evolve their craft as AI changes what great engineering looks like.
• You'll build team culture: designing sustainable on-call rotations, managing capacity with care, developing engineers at every seniority level, and modelling the work-life balance you want your team to have.
• You'll contribute to the wider org: shaping hiring standards, participating in engineering guilds, partnering with Product, Design, QE, and DevOps, and representing your team's perspective in quarterly planning and cross-functional forums.

What We're Looking For

You may be a good fit if you have:

• 3+ years managing engineering teams of 5 or more, with a track record of hiring, developing, and retaining engineers in a high-growth environment
• Experience building hiring pipelines from scratch — role profiles, structured interviews, offer negotiation, and intentional onboarding
• Demonstrated career development impact: you can speak concretely about engineers you've grown from mid to senior, or senior to staff
• Performance management experience including difficult feedback, written reviews, and PIPs
• Strong software engineering background — you've written production code and can hold a genuine conversation about systems design, API design, and data modelling trade-offs
• Working understanding of distributed systems, microservices, event-driven patterns, and CI/CD
• Remote-first leadership experience: you've built real trust and cohesion across timezones without geographic proximity
• A clear point of view on what engineering management means in an AI-first organisation — what changes about coaching, metrics, code review, and quality when 50–70% of code is AI-generated
• Experience working with or alongside teams using AI coding tools (Claude Code, GitHub Copilot, Cursor, or equivalent)

Strong candidates may also have:

• Familiarity with legacy modernisation — monolith decomposition, migration strategies, delivering features while re-platforming underneath
• Experience with revenue management, dynamic pricing, or B2B SaaS for enterprise hospitality
• Hands-on knowledge of our stack: Java/Spring Boot, TypeScript/React, Next.js, GraphQL, MongoDB, AWS
• Exposure to ML or data-intensive systems: real-time analytics, pricing optimisation, low-latency data processing

Why Duetto?

• You'll be managing at the frontier of AI-first engineering. With 50–70% of code AI-generated and custom agents and agentic workflows already in production, this is a rare opportunity to define what great engineering management looks like when code generation is no longer the bottleneck.
• The transformation is real and consequential. Live monolith decomposition, a frontend re-platform, and an AI-first shift — all simultaneously. These are the moments that define engineering careers and management reputations.
• Clear growth path. EM → Senior EM → Director of Engineering. Duetto promotes from within and takes management seriously as a discipline, not a consolation prize for engineers who stopped coding.
• The work matters. Your teams build systems that process real-time pricing decisions for global hotel brands. It's visible, high-stakes, and genuinely interesting.
• Benefits worth having. Equity participation, comprehensive health, dental and vision coverage, home office stipend, generous PTO, and a learning and development budget.

The Details

• Location: Croatia
• Work model: Remote, distributed across EMEA and Americas timezones
• Reports to: Director of Engineering / VP of Engineering
• Direct reports: 5–10 engineers (1–2 teams)

Duetto is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by applicable law.

Sound like you?

You don't need to have done everything on this list. If you're a people-first leader who's technically credible, genuinely curious about AI-augmented engineering, and energised by the idea of leading teams through real transformation — we'd love to hear from you.

#LI-REMOTE

THE ROLE 

The Senior Application Security Engineer is a key member of Cognism’s Information Security Team, reporting into the Application & Infrastructure Security Manager. Your mission is to embed security by design across our engineering and product organization by integrating modern application security practices throughout the full development lifecycle. We focus on building secure, scalable, and resilient systems while enabling the business to innovate quickly and safely. It is to drive a culture where the fastest path for our engineers is the securest path. 

You will work closely with Product, Engineering, Architecture, and Data teams to understand risks within our platform, including risks introduced by AI powered features, and ensure the right controls, guardrails, and security patterns are built into the product at its inception – all the while ensuring a balanced approach to the product experience that our thousands of large global enterprise customers use every day. 

This role is ideal for a senior IC who is technical, collaborative, and pragmatic, with the ability to influence engineering teams while driving hands on improvements to Cognism’s secure SDLC. 

KEY RESPONSIBILITIES 

Security by Design & Product Integration 

• Partner with Product, Web and Data Engineering teams from the ideation stage to ensure security requirements are considered early in feature and model design.
• Translate product and application risks into actionable security controls, making recommendations repeatable to build guardrails and guidance that product, design, and engineering teams can apply as they scale and build the products in the teams they own.
• Help shape security acceptance criteria and guide engineering teams during design reviews and backlog planning. 

Application Risk Assessment & AI Security 

• Identify and assess application risks across Cognism’s SaaS platform, data processing pipelines, including emerging risks associated with AI/ML capabilities.
• Contribute to AI feature reviews and participate in AI risk assessments to ensure responsible and secure use of models, in a way that balances the need to innovate and challenge the status quo in AI implementation.
• Assess and pragmatically recommend mitigations for security risks in data pipelines, model-training workflows, feature stores, and ML systems, ensuring strong controls for data access, data lineage, model integrity, and protection of sensitive datasets. 

Secure SDLC & DevSecOps Enablement 

• Partner with our engineering and platform team to embed security guardrails into our software development lifecycle and agile engineering workflows.
• Partner with engineering teams to integrate and optimize security tooling into CI/CD pipelines (SAST, SCA, DAST, container scanning, IaC scanning).
• Drive automation and developer-friendly security processes that minimize friction and support rapid delivery. 

Threat Modelling & Architecture Support 

• Conduct and facilitate a self-serve, risk-driven approach to pragmatic threat modelling sessions for new features, services, and AI components.
• Conduct threat modelling for data architectures, including ingestion, transformation, storage, streaming, and ML model deployment patterns, ensuring data confidentiality, integrity, and responsible use.
• Provide hands-on application security guidance to engineering teams, helping them implement secure APIs, microservices, data flows, and integrations.
• Maintain and expand Cognism’s secure coding standards, guidance, and reusable security patterns. 

Application Security Testing & Engineering 

• Perform hands-on security testing (manual and automated) for web applications, microservices, APIs, and cloud components.
• Plan, coordinate, and oversee penetration tests, red team exercises, and third-party security assessments, ensuring findings are addressed and tracked.
• Validate findings, assist with prioritization, and partner with engineering teams on remediation strategies. 

Collaboration, Education & Influence 

• Work directly with product squads, acting as a trusted advisor and embedded security partner. Take the time to understand what other teams are working on, what business priorities are, and partner with teams to recommend risk mitigations that balance risk with opportunity and that take into account the threat landscape. 
• Deliver security training, workshops, and guidance to improve engineering teams’ security maturity.Communicate security risk and tradeoffs clearly and constructively to technical and nontechnical stakeholders. 

CORE COMPETENCIES 

• Strong technical depth in application security, cloud security, and secure development.
• Understanding of modern data stack components (e.g., data pipelines, feature stores) and the ability to collaborate effectively with data practitioners.
• Deep understanding of communication protocols used for web development is a must-have.
• Hands on experience with web application development, specifically for back-end development is a must-have competency. 
• Risk-Based Prioritization: Ability to distinguish between theoretical security risks and actual business threats, demonstrating a "risk-driven" rather than "compliance-driven" mindset. Comfortable balancing security risk with product and commercial realities.
• Contextual Communication: Capacity to translate complex technical vulnerabilities into business-impact stories that resonate with non-technical stakeholders and product owners. 
• Collaborative Conflict Resolution: Proven track record of approaching engineering friction with transparency and pragmatism, balancing a firm stance on security with a deep care for the developer experience. Pragmatic problem solver with a growth mindset and bias toward action.
• Architectural Empathy: Ability to put yourself in the position of your users (the engineers) to build security guardrails that are repeatable and embedded into existing workflows rather than added as hurdles. 

EDUCATION & EXPERIENCE 

• 5–10+ years of experience in Application Security, Product Security, or Security Engineering roles.
• Strong experience securing cloud native SaaS platforms (AWS preferred) and Data pipelines. 
• Handson experience with secure coding, application testing, and CI/CD security automation.
• Experience working closely with engineering and product teams in agile environments.
• Familiarity with security frameworks such as OWASP ASVS, OWASP Top 10, NIST, ISO 27001/2.
• Experience evaluating and securing AI/ML enabled features is a strong advantage.
• Experience in SME or high-growth SaaS environments preferred.

About Vumedi:

Vumedi is the largest video education platform for doctors worldwide, dedicated to advancing medical education through innovative video-based learning. Our mission is to empower healthcare professionals by providing them with access to the latest clinical knowledge and surgical techniques from experts around the globe. We curate a vast library of high-quality educational content, enabling users to enhance their skills, stay informed about industry trends, and improve patient outcomes. We are headquartered in Oakland, CA, and have additional offices in Minneapolis, MN, and Zagreb, Croatia.

We're hiring an Engineering Manager to lead the development of our digital platform and products at this critical stage of Vumedi’s growth. 

Why join Vumedi right now?

• Build technology that matters in a fast-scaling Silicon Valley digital healthcare company: Your work directly impacts how doctors across the world learn and make decisions that save lives.
• Grow as we grow: Be part of a company in an accelerated growth phase, where expanding teams, products, and markets create real opportunities for ownership, leadership, and career progression.
• Build with AI: Work on applied LLM systems - from intelligent search to AI-driven content agents - and shape how AI transforms medical knowledge delivery.
• Own your craft end-to-end: Take full responsibility for building systems that scale globally and power mission-critical workflows.
• Collaborate globally: Join a world-class team of passionate engineers on modern tech stack which will further drive your career development.
• Have real product impact: Influence the direction of product development by collaborating closely with product and leadership teams.

About the role:

As an Engineering Manager you will collaborate with your team to work on the video technology platform. Your time will probably be divided between recruiting for your team, developing strong and productive relationships with them and the stakeholders, and networking both inside and beyond the organisation. You will work closely with partner teams including Product, providing and receiving feedback effectively and aligning on shared deliverables as needed.

What you will do:

• Hold regular 1:1 meetings; show support, give encouragement, and help your team members to further develop their technical and professional skills
• Make process suggestions for achieving team goals
• Be a role model; set the tone through own actions in creating an environment where ideas can be shared, questions can be asked, and individuals are accountable for their own actions
• Recruit high-impact people
• Assign tasks to help your team meet their career development plans
• Participate in the performance review process; recognize and reward other’s work accomplishments
• Stay up-to-date with industry trends, emerging technologies, and best practices in software engineering to drive innovation within the team and the company
• Work closely with product managers, designers, and other stakeholders to define product requirements
• Be an active member of the wider engineering community; share knowledge through community talks and help with brand visibility

Who you are:

Required Qualifications

• You have 10+ years of experience in the web development industry
• You have 4+ years experience and success leading engineering teams and you’ve done hiring, managing performance, supported your team members career development, and provided coaching
• You have excellent communication skills so you’re able to motivate and inspire people
• You can effectively hire and retain a successful team
• You’re goal oriented; you’re able to focus and guide others in accomplishing their work objectives
• You are thoughtful and emphatic leader and so you can effectively partner with others in the organization
• You are adaptive and know how to choose an approach appropriate for the moment
• You understand how to give and receive supportive, constructive feedback 
• BS/MS degree in Computer Science or similar

Preferred Qualifications:

• Experience working in dynamic startup-like environments
• Experienced growth from early stage to a mature business
• Nice to have: familiarity with Django or other modern Python web frameworks, as well as familiarity with React or other modern JavaScript/TypeScript stacks

You can expect:

The base salary range for this role is determined by a number of factors, including but not limited to skills and scope required, unique relevant experience, and job-related skills.

Cash salary is but one component of our compensation package. It’s inclusive of base salary, education budget, supplemental health insurance, free meals allowance, work from an alternative workplace allowance, occasional awards - Christmas bonus, and an annual bonus.

We also offer stock options as part of our compensation package, giving you the opportunity to share in the long-term success and growth of the company.

This is a hybrid role, working 3 days a week (Monday, Wednesday, and Friday) in our Zagreb office.

We’re looking for a Senior Product Manager with a passion for mobile games and a proven track record of creating and delivering engaging, commercially successful gaming content. You’ll own the product vision and roadmap for the Content Creation product area, leading cross-functional game studios to drive growth, retention, and monetisation.

As a senior voice in the product team, you’ll balance player delight with commercial performance - turning insights into actions and ensuring our games remain fun, fresh, competitive, safe and compliant.

What we’re looking for:

• 5+ years of product management experience, with at least 2 years in mobile or iGaming games development.
• Visionary and strategic leader with a hands-on approach, known for ambitious thinking and natural problem-solving.
• Proven track record of leading cross-functional game studios, aligning on goals, timelines, and deliverables.
• Strong analytical mindset, with experience using tools like Tableau, Looker, Amplitude, or similar.
• Deep understanding of game mechanics, player behaviour/psychology, live ops, and engagement strategies.
• Passionate about games - you play them, understand the market, and have sharp insights on what makes a game great.
• Comfortable operating in fast-paced, agile environments.
• Proactive and curious, with strong attention to detail and a willingness to learn.
• Excellent communication skills, able to coordinate across teams and serve as a central point of contact for stakeholders.
• Bonus: Experience scaling game studios, regulatory/compliance, balancing game economies, or launching titles globally.

What you’ll be doing:

• Define and execute the product strategy and roadmap, prioritising high-impact initiatives for in-house gaming content to drive key outcomes and achieve OKRs.
• Own and optimise core KPIs, including DAU, LTV, retention, and monetisation performance.
• Communicate product vision and performance to senior leadership, ensuring cross-departmental alignment and facilitating stakeholder input on the content strategy.
• Lead cross-functional squads - including designers, engineers, QA, artists, and analysts - to deliver games and features that enhance both player experience and commercial outcomes.
• Drive GTM, Live Ops, and marketing initiatives, leveraging high-trust relationships with local market stakeholders to ensure regional relevance and optimal product-market fit.
• Define a hypothesis-driven development process, partnering with Research and Experimentation teams to validate concepts via rigorous data analysis, using multiple research methods, before committing resources.
• Translate user research, data analytics, and market trends into actionable product opportunities and strategic insights.
• Lead the Product Development Lifecycle, acting as a primary escalation point to mitigate risks and remove technical or operational blockers.
• Champion a player-centric culture while maintaining a rigorous focus on achieving overarching business objectives, including active involvement in product UAT.
• Mentor and manage other Product Managers, fostering professional growth and establishing departmental best practices.
• Manage the product backlog and author comprehensive PRDs, ensuring all development work is ruthlessly prioritised based on validated hypotheses, player value, and projected ROI.
• Perform deep-dive performance analysis using SQL (Snowflake) and BI dashboards to identify and execute on-game optimisation opportunities.