Software Engineer III  ·  JPMorgan Chase

Aashutosh
Dahal

Get in touch View experience
Drag to rotate ∞
Scroll
01 — About
Aashutosh Dahal
Aashutosh Dahal · JPMC SWE III

Results-driven Software Engineer III with expertise in building scalable, high-performance financial systems. Currently at JPMorgan Chase, architecting microservices-based trading platforms processing millions of transactions daily.

Specialized in microservices architecture, distributed systems, and cloud-native DevOps. Strong background in algorithmic problem-solving and system design — with a demonstrated ability to lead technical initiatives and mentor junior engineers.

BS in Computer Science with a Minor in Mathematics from the University of New Mexico. Passionate about engineering systems that are not just functional, but built to last.

40%
Latency reduced
500K+
API requests/day
99.7%
System uptime
02 — Tech Stack

Tools of the trade

Languages
JavaPython TypeScriptJavaScript SQLGo ScalaC++
Frameworks & Libraries
Spring BootReact AngularNode.js DjangoFlask HibernateJUnit Mockito
Cloud & DevOps
AWS EC2AWS Lambda AWS S3AWS ECS DockerKubernetes JenkinsGitLab CI/CD Terraform
Databases & Observability
PostgreSQLMongoDB RedisCassandra DynamoDBApache Kafka RabbitMQElasticsearch GrafanaPrometheus
03 — Current Experience

Where I am building

Software Engineer III
JPMorgan Chase & Co.
June 2025 — Present
Architected microservices-based trading platform processing millions of daily transactions — reduced latency 40% via Spring Boot and Redis caching.
Led migration of legacy monoliths to AWS with Docker and Kubernetes, achieving 99.7% uptime and 60% faster deployments.
Migrated legacy TIBCO EMS middleware to Amazon SQS, enabling cloud-native event-driven processing and cutting operational overhead.
Built real-time streaming pipelines with Apache Kafka and AWS Lambda for instant transaction processing and risk analytics.
Designed RESTful APIs serving 500K+ daily requests at sub-100ms latency, integrated with React front-ends.
Spearheaded CI/CD adoption with Jenkins and GitLab — automated pipelines reduced production incidents by 75%.
Optimized PostgreSQL queries and implemented sharding strategies, improving query performance by 50% for high-volume financial data.
Mentored junior engineers on system design, code reviews, and performance optimization best practices.
04 — Contact

Let's build
something great

Open to new opportunities, collaborations, and interesting conversations. I'd love to hear from you.

aashutoshdahal268@gmail.com
LinkedIn Email +1 469 708 6541