Staff Backend Engineer - Promos

Hard Rock Digital•United States, FL

About The Position

Hard Rock Digital is building online sportsbook, casino, and social gaming products for millions of consumers. The Staff Backend Engineer will own technical direction for backend capabilities in the Promos domain within a shared service and cloud ecosystem. The role addresses complex distributed-systems problems, guides the evolution of APIs, events, data, and services, and raises engineering standards while remaining hands-on. The engineer works across 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. Staff-level impact includes creating clarity beyond one team, developing other engineers, and taking accountability for organizational outcomes. The role includes setting domain architecture and strategy; building scalable promotion lifecycle capabilities; leading delivery, quality, and production operations; advancing responsible AI-assisted engineering; and serving as a trusted technical advisor and mentor. The position is expected to balance product delivery, technical debt, scalability, and platform investment through pragmatic decisions and measurable outcomes.

Requirements

Typically 7+ years of software engineering experience, including substantial experience designing and operating distributed backend systems.
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 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 practical understanding of evaluation, hallucination risk, privacy, security, and responsible human review.
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.

Nice To Haves

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.

Responsibilities

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 owners of shared capabilities, including identity, payments, compliance, messaging, and platform services, while maintaining clear ownership boundaries.
Guide architecture evolution and modernization, balancing product delivery, technical debt, scalability, and platform investment.
Lead major restructuring initiatives through planned iterative delivery; define target states, sequence work, surface dependencies and risks, and update delivery dates as evidence changes.
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 volumes using appropriate consistency, caching, asynchronous processing, rate controls, and graceful degradation.
Remain hands-on with difficult problems, turn ambiguity into iterative delivery, delegate effectively, and correct work that is off course or not producing value.
Model and raise standards for code review, 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, and turn incidents into systemic improvements.
Drive responsible adoption of AI-assisted development across discovery, implementation, testing, documentation, debugging, and review, and measure its effects on quality, speed, learning, and developer experience.
Identify useful product and operational applications for AI, assess feasibility and model risk, and establish guardrails for evaluation, confidential data, human accountability, and production safety.
Advise Product and Engineering teams proactively, identify risks and opportunities early, make recommendations informed by customer, operational, and market insight, 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, and lead change with calm ownership, constructive conflict, clear commitments, and learning without blame.