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LeadFull-timeJavaAWSGCPKubernetesTerraformMongoDBRedisAgileGitAI
Salary Range
$30,600 - $41,400 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are looking for a Staff Software Engineer to join our team at Clari + Salesloft. You will be a key member of our fast-growing and high-performing team in India, helping to build the industry’s first Predictive Revenue System that enables humans and AI to work together to make smarter decisions and drive consistent growth.
Key Responsibilities
- →Shape future-proof interfaces that are easy to build against and meet the requirements of client-facing teams
- →Brainstorm with Product Managers, Designers, Frontend Engineers, and other cross-functional partners to conceptualize and build new features for our growing user base
- →Produce high-quality results by leading or contributing heavily to large cross-functional projects that have a significant impact on the business
- →Debug production issues across services and multiple levels of the stack, and up level the observability and reliability of the overall system
- →Improve engineering standards, tooling, and processes
Requirements
- ✓8+ 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)
- ✓Demonstrated experience working with cloud infrastructure, ideally AWS or GCP, including Kubernetes clusters (GKE/EKS), serverless architectures, and managed services (e.g., Lambda, Cloud Run, ECS)
- ✓Proven experience with distributed data infrastructure: message queues (Kafka, Kinesis), caching systems (Redis, Memcached), database optimization, and building resilient, fault-tolerant architectures
- ✓Familiarity with SQL (postgres) / NoSQL (MongoDB) and data warehouse modeling; capable of managing complex data queries, joins, aggregations, and transformations
- ✓Solid understanding of platform monitoring and optimization, including identifying performance bottlenecks, latency optimization, cost management, and scaling high-throughput API services efficiently
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