Rewards Network

DevOps Engineer

• Support and improve deployment pipelines to production and staging environments, with a focus on reliability, consistency, and reducing toil.
• Troubleshoot and resolve Kubernetes cluster and application-level issues, Docker containers, and Linux-based environments to support applications and services.
• Leverage Grafana, Prometheus, and Elasticsearch to monitor, diagnose, and improve system health.
• Build and improve internal tooling and automation to improve developer experience.
• Partner with development teams to address infrastructure and deployment needs, both planned and ad hoc.
• Maintain and improve AWS infrastructure using Terraform and Atlantis.
• Manage secrets and security operations with HashiCorp Vault.
• Participate in an on-call rotation to support production systems and incident response.
• Collaborate across teams to improve system observability, resilience, and automation.
• Document processes and contribute to knowledge sharing to improve engineering efficiency.

Senior Site Reliability Engineer

Product Manager

• Lead end-to-end project management for complex, cross-functional initiatives spanning Product, Engineering, Data, Partner Management, and Operations.
• Define and maintain project plans, timelines, milestones, and dependency maps; drive accountability against committed dates and quality bars.
• Identify, track, and proactively mitigate risks and issues; escalate appropriately and recommend trade-offs when scope, schedule, or resources require rebalancing.
• Drive intake, prioritization, and capacity planning processes — working with Product leadership to ensure the right work is sequenced against available resources.
• Own program-level reporting and status communication for executive and stakeholder audiences; translate complex delivery details into clear, decision-ready summaries.
• Manage cross-team dependencies with internal partners and external integrations (e.g., loyalty program partners), ensuring alignment on requirements, timelines, and acceptance criteria.
• Continuously improve project management practices, tools, templates, and processes.
• Champion a culture of clear ownership, transparent communication, and continuous improvement across the Product organization.

Senior Product Manager

Customer Success Manager

• Oversee the customer journey for an assigned portfolio of accounts, from onboarding a new customer through ongoing support, with the goal of maximizing customer satisfaction and loyalty.
• Proactively identify and address customer issues, leading to minimized churn. (Examples: missing tickets, accounts receivables, managing exclusions.)
• Respond to customer requests for support, guiding clients through product features and strategies to maximize the benefits they receive from our services.
• Communicate with clients to ensure they are realizing the full value of our services, thereby improving Net Promotor Scores (NPS)
• Identify opportunities within the assigned portfolio to introduce and upsell products (i.e. Cash)
• Work closely with the regional manager and sales teams to execute strategies that enhance the customer satisfaction and business growth.
• Monitor account health metrics and provide insights to leadership on portfolio status and renewal/conversion opportunities.
• Share customer feedback and insights with the internal teams to shape future offerings.

Client Success Manager

• Define and manage the product roadmap for consumer-facing experiences across web, mobile web, native apps, and email/SMS/push channels — including loyalty mechanics, member onboarding, search and discovery, and post-dining engagement.
• Define and evolve engagement strategy: how members earn, track, and redeem rewards across our 30+ partner programs in ways that feel rewarding, intuitive, and drive habitual engagement
• Translate consumer insights, behavioral data, and qualitative research into prioritized backlogs, user stories, and clear acceptance criteria for engineering teams.
• Partner with engineering and design to ship features iteratively, balancing speed of learning with quality of experience.
• Define and instrument success metrics — activation, retention, dining frequency, member LTV, NPS — and use experimentation (A/B testing, holdout cohorts) to validate hypotheses and inform roadmap decisions.
• Collaborate with Marketing, Lifecycle, and CRM teams on go-to-market and lifecycle communication strategies that drive feature adoption and member engagement.
• Work with Partner Management to ensure our consumer experience aligns with the brand standards and member expectations of airline, hotel, and retail loyalty partners.
• Champion the voice of the consumer across the organization through user research, member feedback synthesis, and competitive analysis of loyalty and dining apps.
• Stay current on trends in consumer loyalty, engagement mechanics, gamification, and dining technology to identify opportunities for differentiation.
• Manage cross-functional alignment, ensuring transparent communication and coordination between product, engineering, marketing, partner management, and business stakeholders.

Product Manager, B2C Offers

Backend Engineer

• Lead the development of scalable back-end systems to support platform services.
• Architect RESTful APIs and microservices using functional programming to ensure reliability and maintainability.
• Build real-time data pipelines to enable efficient platform operations.
• Optimize databases for performance and data integrity.
• Mentor team members on functional programming practices and system design for high-quality, testable code.
• Collaborate with DevOps and data teams to align on platform performance and operational needs.
• Implement security measures to safeguard sensitive platform data.
• Oversee projects from design to deployment, ensuring alignment with business goals.
• Enhance CI/CD processes to maintain platform reliability.
• Research advanced functional programming techniques to improve system performance.

Senior Scala/Python Engineer

Artificial Intelligence

• Configure and train AI agents. Define how agents think, respond, and act — setting instructions, topics, guardrails, and behaviors that make them effective in real operational contexts.
• Configure AI workflows and agent behavior across a variety of platforms including Salesforce Agentforce, Microsoft Copilot Studio, Claude, and Power Automate — translating business requirements into instructions, guardrails, and responses that drive operational performance.
• Maintain deployed solutions and monitor ongoing performance — tracking output quality, identifying gaps, and keeping solutions functioning reliably across user groups.
• Suggest and implement enhancements based on user feedback and operational performance data, maintaining a continuous improvement cycle between end users and deployed tools.
• Drive AI literacy across Sales and Operations. Develop best-practice guidance and deliver hands-on enablement that helps teams get more out of the tools they use, improving both adoption depth and output quality.
• Gather and close the feedback loop. Actively collect input from end users, translate their experience into prioritized improvements, and serve as the primary conduit between the people using the tools and the people building them.
• Coordinate with Product and Operations teams on efficiency initiatives — ensuring agent training and configuration aligns with platform implementation and RTB process requirements.
• Evaluate emerging AI tools and platforms. Stay current on the AI landscape and bring forward-looking recommendations on new capabilities, tools, and enhancement opportunities to leadership.
• Support change management and adoption by developing communications, training materials, and rollout plans that drive sustainable adoption of new AI workflows and tools across the organization.

AI Operations Specialist

Data Scientist

• We're looking for a Senior Data Scientist to help lead the technical evolution of a large-scale personalization and assignment platform.
• You'll design and own the data systems that match members to offers — from batch pipelines processing hundreds of millions to billions of records to the scoring frameworks that decide what each member sees.
• This is a senior individual contributor role with technical leadership scope.
• You won't have direct reports, but you'll help set technical direction, guide junior data scientists and engineers, and own workstreams end-to-end.
• The platform is actively evolving toward ML-driven personalization and generative AI, and we're looking for someone who wants to help shape that direction.

Senior Data Scientist – Data & Personalization Platform

• Oversee SLAs across the Intelligent Assignment Engine (IAE) pipeline (batch completion, feed delivery, attribute freshness, assignment turnaround) and drive activity-based classification and tiering of members and merchants, ensuring definitions, thresholds, and refresh cadences are aligned with business and downstream consumption needs.
• Design and build the offer priority scoring framework used to rank eligible offers per member, including score definition, input features (member attributes, merchant attributes, behavioral signals, business priorities), weighting logic, and validation against business objectives, and evolve the scoring model as personalization and ML capabilities mature.
• Provide technical leadership and execution guidance across the IAE pipeline, including nightly batch assignment processing, member and merchant attribute management, eligibility evaluation logic, and S3-based data feed production.
• Lead the design, generation, and ongoing management of customer segmentation and feature pipelines, including member group construction, attribute bucketing strategy, and the production of feature sets used for offer eligibility evaluation and targeting.
• Lead the design and optimization of large-scale data processing workflows handling hundreds of millions to billions of records, including partitioning strategy, bulk ingestion, and performance tuning.
• Own the evolution of the IAE attribute pipeline including member and merchant attribute design, metric definition, bucketing strategy, and ongoing quality validation, and drive alignment with business stakeholders on open decisions (tier boundaries, bucket values, time windows, metric design).
• Provide architectural guidance on the development of a real-time synchronous API layer for offer assignment, including near-real-time member enrollment and user-triggered assignment events, and ensure sound integration with the broader batch pipeline.
• Oversee the analytics mart maintenance and incremental build-out post-MVP, ensuring data models remain accurate, performant, and aligned with evolving reporting needs.
• Act as the primary technical bridge between business stakeholders (product, marketing, finance) and the IAE/data engineering team, translating business requirements into data pipeline and attribute requirements and translating data constraints back into business-legible terms.
• Guide and review the work of junior data scientists and data engineers on the IAE team, providing technical direction and prioritization support without formal people management responsibility.
• Collaborate with the Nova platform team and engineering to ensure IAE outputs meet downstream data contracts, S3 feed schemas, and serve the offer assignment pipeline reliably.
• Define and maintain data contracts between IAE and downstream consumers (Nova, analytics marts, dashboards).
• Identify and surface data quality risks, pipeline gaps, and go-live readiness issues across IAE's attribute and assignment outputs.
• Build and maintain documentation of IAE architecture, data models, pipeline logic, attribute definitions, and feature generation processes to reduce key-person dependency and support team continuity.
• Contribute to the future development of offer personalization and recommendation capabilities, including A/B testing frameworks, behavioral modeling from member dining habits, and an informed point of view on how ML and generative AI approaches can evolve the assignment and eligibility engine over time.

Senior Data Scientist – Intelligent Assignment Engine

Sales Development Rep

• Follow up on marketing generated leads through phone, email, and social channels.
• Identify and research lists of prospective restaurants.
• Complete a high volume of daily activities to generate sales meetings.
• Build a strong pipeline of qualified leads for our field sales representatives.
• Track all touchpoints and outcomes in our CRM (Salesforce)
• Provide feedback on sales strategy and efficacy of call scripts and value prop.

Sales Development Representative

Recruitment

• Lead full-cycle recruiting across corporate functions, including Finance, IT, Product, Marketing, Data Science, Customer Success, and Client Relations
• Partner with hiring managers and business leaders to understand hiring needs, define role requirements, and develop effective recruiting strategies
• Build and execute proactive sourcing strategies using tools such as LinkedIn and other platforms to attract high-quality, diverse talent
• Manage the end-to-end candidate experience, ensuring timely communication, strong engagement, and a positive brand impression
• Facilitate interview processes, drive alignment among stakeholders, and guide hiring decisions
• Leverage data and reporting to monitor pipeline health, improve recruiting effectiveness, and inform business decisions
• Provide market insights and talent intelligence to influence hiring strategies and workforce planning
• Represent Rewards Network at recruiting events, networking events, and industry engagements to build brand awareness and talent pipelines
• Contribute to employer branding initiatives to strengthen Rewards Network’s position as an employer of choice
• Partner cross-functionally with HR and business leaders on broader talent initiatives

Corporate Recruiter

Financial Planning and Analysis

• Prepare and deliver monthly and quarterly financial reports for senior management, ensuring accuracy and timeliness.
• Assist in month-end close activities, partnering closely with accounting, legal and operations
• Conduct in-depth analysis of financial results and KPIs to identify trends, risks, and opportunities
• Automate and continuously improve models to streamline reporting/planning processes to reduce cycle times and improve efficiency.
• Support the annual budgeting and quarterly forecasting processes
• Develop and maintain financial models to support strategic initiatives and perform ad hoc analysis
• Collaborate with teams across data science, product, and technology to timely resolve any data integrity issues

Financial Analyst, FP&A

• Develop and maintain back-end features for web applications using modern languages and frameworks.
• Design and build scalable, maintainable system architectures, including RESTful microservices.
• Integrate and manage relational databases to ensure efficient data storage and retrieval.
• Implement event-driven and streaming solutions to support real-time data processing.
• Write high-quality, well-tested code to ensure reliability, performance, and scalability.
• Partner with cross-functional teams to deliver solutions aligned with business goals and timelines.
• Ensure security best practices are embedded across back-end systems and data flows.
• Contribute to continuous improvement of development processes, tools, and best practices.