Software Engineer, Backend Developer, Cloud Engineer - Software

A rapidly growing, venture-backed technology organization is seeking Senior and Staff Software Engineers to help establish and scale its Boston engineering presence. This team is building a modern, AI-powered customer data and CRM platform that enables businesses to better manage, activate, and derive insights from their customer data. The role is heavily focused on backend engineering, distributed systems, AWS infrastructure, and high-scale application development
, while also contributing to new product experiences built with React and Node.js
.

This opportunity is ideal for engineers who have built and operated large-scale production systems at leading technology companies or high-growth startups. The organization is specifically interested in candidates who have worked on core platform, infrastructure, database, analytics, billing, or data-intensive products where scalability, performance, and reliability are mission-critical.

The engineering team is tackling complex technical challenges around real-time data processing, cloud infrastructure, and platform scalability. Engineers will have the opportunity to influence architecture, build systems that process large volumes of data, and help shape the technical direction of a growing product organization. This is an excellent opportunity for candidates who thrive in fast-moving environments and are passionate about solving difficult distributed systems problems while building customer-facing applications that deliver measurable impact.

• 6+ years of professional software engineering experience (Senior level) or 10+ years (Staff level)
• Expert-level proficiency with Type Script and Node.js
• Extensive experience designing and operating scalable backend services in production environments
• Strong experience building on AWS (EC2, ECS/EKS, Lambda, S3, RDS, DynamoDB, Cloud Watch, IAM, or similar)
• Experience designing distributed systems and microservices architectures
• Proven track record improving system performance, throughput, latency, and reliability
• Experience operating services handling high-volume traffic and large-scale datasets
• Strong understanding of cloud-native application development and observability practices
• Experience working on teams that own critical online databases, APIs, or high-scale backend services
• Familiarity with modern frontend technologies including React
• Strong communication and collaboration skills in cross-functional environments
• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience

• Experience at recognized technology companies or product-focused engineering organizations
• Background working at startups whose products solve infrastructure, database, analytics, observability, billing, or scalability challenges
• Experience with real-time data infrastructure technologies such as:
  • Kafka
  • Click House
  • Apache Flink
  • Apache Spark
  • Similar streaming or data processing platforms
• Experience building analytics, customer data, platform, or infrastructure products
• Exposure to event-driven architectures and streaming systems
• Experience mentoring engineers and driving technical strategy
• Strong understanding of database internals, data modeling, and performance optimization
• AI/ML product experience is a plus

• 50% Type Script / Node.js Backend Engineering
• 20% AWS Infrastructure & Cloud Architecture
• 15% Distributed Systems & Scalability Initiatives
• 10% React Application Development
• 5% Technical Leadership & Mentorship

• 40% Designing and building scalable backend services
• 20% Improving system performance, reliability, and latency
• 15% Building and enhancing cloud-native infrastructure on AWS
• 15% Collaborating with product and engineering teams on new features
• 10% Architecture reviews, mentoring, and technical leadership

Candidates should be prepared to discuss:

• Specific scalability and performance metrics they have owned or influenced
  • Throughput such as 1,000+ queries, requests, or entities processed per second
  • Latency improvements and measurable reductions in p95/p99 response times
  • Reliability, availability, and operational metrics
• Real-time data infrastructure experience
  • Kafka
  • Click House
  • Flink
  • Spark
  • Other large-scale streaming or analytical data platforms
• Ownership experience
  • Managing production databases
  • Operating mission-critical backend services
  • Scaling distributed systems in production environments
• Architectural…