Staff Backend Engineer - Promos

What are we building? Hard Rock Digital is a fiercely focused team working to become the best online sportsbook, casino, and social gaming company in the world. We're building a deeply curious team with a passion for learning, operating, and building new products and technologies for millions of consumers. We're customer-obsessed — we care about each customer interaction, experience, behavior, and insight, and strive to ensure we're always acting authentically. Rooted in the kindred spirits of Hard Rock and the Seminole Tribe of Florida, Hard Rock Digital taps a brand known the world over as the leader in gaming, entertainment, and hospitality. We're taking that foundation of success and bringing it to the digital space - ready to join us? What’s the position? We’re looking for a Staff Backend Engineer to own technical direction for backend capabilities within the Promos domain, working within our shared service and cloud ecosystem. You will solve complex distributed systems problems, guide the evolution of APIs, events, data, and services, and raise the engineering bar across teams while remaining close to the code. Working across Product, Mobile, Web, Data, QA, Platform, Security, Compliance, and Operations, you will turn ambiguous needs into durable strategies and guide critical initiatives from discovery through production. Staff level impact means creating clarity beyond one team, developing other engineers, and being accountable for organizational outcomes, not only implementation. Your responsibilities will include: Technical strategy and architecture Own backend technical direction for the assigned product domain, such as Promos, while aligning with shared platform, cloud, data, and service standards. Partner with Principal and Staff Engineers and teams that own shared capabilities such as identity, payments, compliance, messaging, and platform services, integrating those capabilities while maintaining clear ownership boundaries. Guide architecture evolution and modernization, balancing product delivery, technical debt, scalability, and platform investment through pragmatic decisions, clear tradeoffs, and measurable outcomes. Lead major restructuring work through planned iterative delivery: establish the target end state before execution, decompose the initiative into sequenced tickets, surface dependencies and risks, and provide credible delivery dates that are updated as evidence changes. Promotional and backend capabilities Build scalable and reliable promotion lifecycle capabilities, including configuration, eligibility, activation, state transitions, rewards, expiration, auditability, idempotency, and recovery. Partner with Product, Mobile, Web, Back Office, Data, and Operations to define service boundaries, API and event contracts, experimentation, success measures, and operational controls. Design resilient services for high traffic and transaction volume, using appropriate data consistency, caching, asynchronous processing, rate controls, and graceful degradation strategies. Execution, quality, and operations Remain hands on with the hardest problems, turning ambiguity into iterative delivery while delegating effectively and correcting work that is off course or not producing value. Model and raise a high bar for code review, using reviews to improve correctness, maintainability, shared understanding, and engineer growth, and advance standards for testing, API design, security, observability, performance, CI/CD, controlled rollout, data migration, and production readiness. Lead diagnosis across services, APIs, databases, caches, queues, and event streams using correlated logs, traces, and metrics, turning incidents into systemic improvements. AI enabled engineering Drive responsible adoption of AI assisted development across discovery, implementation, testing, documentation, debugging, and review, measuring improvements to quality, speed, learning, and developer experience. Identify valuable product and operational uses for AI, assess feasibility and model risk, and establish guardrails for evaluation, confidential data, human accountability, and production safety. Organizational impact and culture Act proactively as a trusted technical advisor to Product and Engineering teams, identifying risks and opportunities early and using customer, operational, and market insight to make clear recommendations and drive decisions to closure. Mentor Senior and Staff Engineers through architectural guidance, reviews, pairing, and reusable knowledge, and contribute technical perspective to senior hiring, capability planning, and career development. Resolve systemic risks, ownership gaps, and missing capabilities by bringing the right people together, and lead change with calm ownership, constructive conflict, clear commitments, and learning without blame. Requirements What are we looking for? The ideal candidate will have: Typically 7+ years of software engineering experience, including substantial experience designing and operating distributed backend systems, plus a degree in Computer Science or a related field or equivalent demonstrated experience. Deep expertise with Java, Spring, and Spring Boot, with a record of establishing patterns and standards adopted by multiple teams. Strong AWS knowledge and experience building scalable, resilient applications across multiple regions and availability zones. Expertise with relational data systems such as PostgreSQL or CockroachDB, including schema design, transactions, migrations, indexing, performance, and consistency tradeoffs. Experience with streaming technologies such as Amazon Kinesis or Kafka and messaging systems such as SQS, RabbitMQ, or ActiveMQ. Experience designing microservice and service oriented architectures and operating containerized workloads with Docker and Kubernetes. Strong judgment around high volume systems, concurrency, idempotency, caching, asynchronous workflows, failure recovery, and backward compatible API and e