Senior Bet Engine Engineer - Low-Latency & Scalable

Penn Interactive Ventures

California (MO)

Hybrid

USD 104,000 - 139,000

Full time

7 days ago

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Benefits offered by this job

Competitive compensation package

Relaxed work environment

Education reimbursements

Career progression

Job summary

PENN Entertainment, Inc. is seeking an experienced software engineer to design, scale, and optimize high‑throughput GraphQL APIs, gRPC services, and SQL workloads powering sportsbook wagering, casino transactions, and financial ledgers.

You will own complex problems, mentor peers, and collaborate across teams to enable scalable, compliant platforms. With a strong focus on reliability, performance, and cross‑service integrations, you’ll help drive architectural decisions while ensuring secure,

Qualifications

Minimum 5 years of experience in software engineering.
Strong foundations in data structures, distributed systems, algorithms, and software design.
Experience with production systems at scale and identifying performance improvements.
Experience with on-call rotations and end-to-end release ownership.
Familiarity with modern web frameworks and API development (Phoenix, Rails, FastAPI, Laravel, Node).
2+ years designing and evolving GraphQL schemas for multi-client surfaces.
Experience with multi-client/white-label platforms and geo-based routing configurations.
Strong relational DB skills (PostgreSQL, MySQL) and data modeling.
Experience with Kubernetes and containerized environments.
Proficient in Git workflows and CI/CD processes.
Experience with testing frameworks (ExUnit, RSpec, Jest, pytest).
Experience with background job processing (Oban, Exq, Sidekiq, Celery).
Experience with asynchronous messaging (Kafka, RabbitMQ, AWS SQS/SNS).
Interest in agentic software development tools and governance.

Responsibilities

Design, scale, and tune GraphQL APIs, low-latency gRPC services, and SQL queries.
Own high-scope technical problems and present proposals to leadership.
Design, architect, and deliver end-to-end features in an agile/scrum setting.
Identify production bottlenecks and drive scalability improvements.
Set up and refine monitoring/alerting in Datadog for owned systems.
Mentor engineers across teams through specs, pairing, and code reviews.
Collaborate with stakeholders to deliver best-in-class products and cost efficiencies.
Bridge internal, third‑party, legacy, and modern systems; manage data migrations and supporting infra.