Principal Backend Engineer - Promo
About the role
Hard Rock Digital is building the world’s best online sportsbook, casino, and social-gaming platform. As Principal Backend Engineer you will own the technical direction for backend capabilities within the Promos domain, working inside 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 hands-on with code.
You will collaborate with Product, Mobile, Web, Data, QA, Platform, Security, Compliance, and Operations to turn ambiguous needs into durable strategies and guide critical initiatives from discovery through production. At the Principal level you are accountable for organizational outcomes, not just implementation: you create clarity beyond one team, develop other engineers, and drive impact at scale.
Responsibilities
- Technical strategy and architecture
- Own backend technical direction for the Promos domain while aligning with shared platform, cloud, data, and service standards.
- Partner with Principal and Staff Engineers and teams that own shared capabilities (identity, payments, compliance, messaging, platform services) and integrate 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 trade-offs, 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: 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; 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; 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; lead change with calm ownership, constructive conflict, clear commitments, and learning without blame.
Requirements
- Typically 10+ years of software engineering experience, including substantial experience designing and operating distributed backend systems.
- 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 trade-offs.
- 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 event evolution.
- Strong engineering judgment across testing, observability, CI/CD, secure development, performance, privacy, and production operations for business-critical systems.
- Hands-on fluency with AI-assisted development and a practical understanding of evaluation, hallucination risk, privacy, security, and responsible human review.
- A record of shaping technical and product strategy, delivering ambiguous multi-team initiatives, communicating clearly with senior stakeholders, and influencing outcomes without relying on formal authority.
Preferred experience
- Experience in sportsbook, casino, online gaming, fintech, banking, or another regulated digital industry.
- Experience building promotion, loyalty, offer, reward, experimentation, or customer-engagement platforms.
- Experience scaling engineering through shared libraries, developer platforms, service templates, internal tooling, or production AI practices.
Benefits
- Competitive pay and benefits.
- Flexible vacation allowance.
- Flexible work from home or office hours.
- Startup culture backed by a secure, global brand.
- Opportunity to build products enjoyed by millions as part of a passionate team.