Principal Engineer – Revenue Management, Intelligence

🔥 15 hours ago

🇺🇸 United States – Remote

💵 $238k - $265k / year

⏰ Full Time

🔴 Lead

🧑‍💻 Full-stack Engineer

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Salesloft

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2011

🤝 B2B

☁️ SaaS

⚡ Productivity

B2B • SaaS • Productivity

Salesloft is a company that provides a sales engagement platform designed to help businesses improve their sales processes and enhance customer relationships. The platform offers features such as email tracking, call logging, and sales analytics, allowing sales teams to engage with prospects more effectively and efficiently. Salesloft integrates with various third-party applications, including Salesforce, LinkedIn, and Microsoft Outlook, to streamline sales activities and improve productivity. The company also focuses on providing reliable services by monitoring and resolving incidents that may impact the use of their platform, ensuring minimal disruption to their users.

📋 Description

• Shape future-proof interfaces that are easy to build against and meet the requirements of client-facing teams • Brainstorm with Product Managers, Designers and Engineers, and other cross-functional partners to conceptualize and build new features for our growing user base • Produce high-quality results by leading large cross-functional projects that have a significant impact on the business • Debug production issues across services and multiple levels of the stack, and uplevel the observability and reliability of the overall system • Own architecture decisions across multiple teams, drive long term technical strategy, and raise the bar for engineering excellence company-wide • Mentor Staff and Senior engineers

🎯 Requirements

• 12+ years of experience in building distributed systems or platform infrastructure designed for high-scale, data-intensive workloads • Expert-level proficiency in Java or a similar object-oriented language and familiarity with infrastructure tooling (Airflow, Kubernetes, Ray, Terraform), service frameworks (FastAPI, gRPC), and observability platforms (Prometheus, Grafana, DataDog, Splunk) • Deep experience with cloud infrastructure, ideally AWS or GCP, including Kubernetes clusters (GKE/EKS), serverless architectures, and managed services (e.g., Lambda, Cloud Run, ECS) • Architected solutions requiring distributed data infrastructure: message queues (Kafka, Kinesis), caching systems (Redis, Memcached), database optimization, and building resilient, fault-tolerant architectures • Expertise with SQL (postgres) / NoSQL (MongoDB) and data warehouse modeling; capable of optimizing complex data queries, joins, aggregations, and transformations • Solid improvements of platform monitoring and optimizations, including identifying performance bottlenecks, latency optimization, cost management, and scaling high-throughput API services efficiently

🏖️ Benefits

• performance bonus • benefits and/or other applicable incentive compensation plans