Senior Software Engineer – Low Latency Applications

We partner with forward-thinking organizations to build technology solutions that scale, delight users, and accelerate business growth. Our global teams bring curiosity, commitment, and technical excellence to every project. We value transparency, autonomy, and impact—empowering every team member to do their best work.

About the role

We’re seeking a Senior Software Engineer with deep AWS and Node.js expertise to join a high-performance motorsport client. The client is building a real-time application that will power live telemetry, timing/scoring, and optical tracking feeds for major automotive partners—and they need a senior engineer to validate the architecture, identify blind spots, and ensure every data point is delivered reliably to consumers.

This is a full-time, fully remote position requiring a minimum of 40 hours per week, Monday through Friday. Candidates must be based in regions that align with the Pacific, Central, or Eastern U.S. time zones.

Responsibilities

• Validate the existing AWS Kinesis architecture—reviewing fan-out patterns, shard configuration, consumer throughput, and delivery guarantees to identify gaps before the platform scales to major automotive partners.
• Identify and remediate blind spots in the real-time data pipeline: dropped records, ordering issues, late or duplicate events, consumer lag, and failure modes that aren’t yet visible or alertable.
• Build and maintain Node.js services that produce, consume, and process streaming data over WebSockets and Kinesis—ensuring robust error handling, retry logic, and end-to-end delivery reliability.
• Design and implement streaming data flows using WebSockets and AWS Kinesis, handling high-frequency telemetry and race event data with low-latency, high-reliability delivery requirements.
• Harden AWS infrastructure across IAM (least-privilege policies, service roles), S3 (storage patterns, lifecycle, access controls), and Kinesis (stream configuration, enhanced fan-out, monitoring)—working within the existing platform architecture.
• Collaborate with data engineers and platform stakeholders to ensure the streaming layer delivers clean, complete, and ordered data that the downstream Databricks Lakehouse platform and consumers can trust.
• Apply AI tooling (Claude) to accelerate architecture review, code analysis, and documentation—using it as a force multiplier across the engagement.
• Produce clear technical documentation of architecture findings, identified risks, recommended remediations, and system design decisions for both engineering and stakeholder audiences.

Requirements

• 6+ years as a software or backend engineer, with a demonstrated focus on distributed systems, real-time streaming, and AWS cloud infrastructure in production environments.
• Expert-level proficiency in Node.js for building production-grade services that produce, consume, and process high-frequency streaming data—including TypeScript, async patterns, and robust error/retry handling.
• Hands-on experience designing and operating WebSocket-based streaming data flows in production; strong understanding of real-time delivery semantics, ordering guarantees, and failure modes.
• Production experience with AWS Kinesis—stream design, shard management, enhanced fan-out, consumer lag monitoring, and delivery reliability at scale. This is the core technical screen.
• Solid working knowledge of IAM (least-privilege, service roles, policies), S3, and Kinesis as a unified platform—able to review, harden, and extend existing infrastructure configurations.
• Strong system design fundamentals—able to review an existing architecture, identify reliability and scalability blind spots, and recommend concrete remediations with clear trade-off reasoning.
• Strong coding proficiency in JS/TS; comfortable writing, reviewing, and refactoring production code across the streaming and integration layer.
• Practical experience using Claude or equivalent AI assistants to accelerate architecture review, code analysis, and documentation workflows.
• Sufficient understanding of downstream data consumers (Databricks, analytics platforms) to ensure the streaming layer delivers what they need—completeness, ordering, low latency, and reliability.
• Strong written and verbal communication skills in English; able to document findings and present architectural recommendations clearly.

Benefits

• Flexible working hours in a remote environment.
• Health insurance (medical and dental) for W2 Employees.
• 401K Contribution.
• A professional development fund to enhance your skills and knowledge.
• 15 days of paid time off annually.
• Access to soft-skill development courses to further your career.

Pay

Salary range: $72,000 - $96,000 annually, with final compensation determined by your qualifications, expertise, experience, and the role's scope.