Aadil Khan

Senior Software Engineer

Falls Church, Virginia, United States5 yrs 7 mos experience

Highly Stable

Key Highlights

Expert in building scalable cloud platforms.
Proven track record in machine learning infrastructure.
Strong background in document processing technologies.

Stackforce AI infers this person is a SaaS and Fintech specialist with expertise in cloud computing and machine learning.

Contact

Skills

Core Skills

Software DevelopmentCloud ComputingPlatform DevelopmentMachine LearningCloud InfrastructureDocument Processing

Other Skills

DockerAmazon Web Services (AWS)KubernetesAWSAzureGCPDynamoDBS3SagemakerSQSAWS TextractJavaPythonOCRGremlin

About

I am currently working as a software engineer at Confluent. My interest lies in working on distributed systems. Email: aadilk97@gmail.com GitHub: github.com/aadilk97

Experience

5 yrs 7 mos

Total Experience

1 yr 11 mos

Average Tenure

1 yr 8 mos

Current Experience

Confluent

Senior Software Engineer

Sep 2024 – Present · 1 yr 8 mos · Remote

Building a secure, scalable and multi-tenant platform that runs all untrusted customer workloads of Confluent Cloud. It supports multiple programming languages and is built across AWS, Azure and GCP.
Reduced workload provisioning latency by 20% by adding warm pool support which eliminated cold start latency of kubernetes pods hosting workloads.
Enabled multiplexing which allowed multiple workloads to be bin-packed on a single k8s pod. This increased the
platform efficiency by allowing a single node to host unto 50% more customer workloads.
Lowered artifact download latency from 5s to ~50ms by implementing a rust based daemonset service that prevents redundant downloads by caching artifacts and mounting them as hostPath volumes on the runtime pod.
Added autoscaling support to the platform by enabling seamless horizontal scaling of workloads based on metrics like pod’s memory and CPU usage. This ensures that customer requests are never throttled.
Designed a rollout solution to apply updates and security patches to live customer workloads with 0 downtime.

DockerAmazon Web Services (AWS)KubernetesSoftware DevelopmentCloud Computing

Appian corporation

2 roles

Software Engineer II

Promoted

Oct 2022 – Sep 2024 · 1 yr 11 mos · McLean, Virginia, United States

Leveraged DynamoDB, S3, Sagemaker and SQS to build a scalable ML Platform that allowed internal teams to develop AI features by providing them with the infrastructure to run training and inference workflows.
Shipped a custom document extraction feature that allows customers to train models customized to their datasets. Training instances were run in Sagemaker and inferences in kubernetes to handle high volume.
Performed outage-less migration of an internal service from being deployed with gitlab runners to ArgoCD thereby saving about 3 hours worth of manual effort per week to deploy the service.
Identified the gap between the current performance metrics and the SLAs required to secure a 7 figure prospect by designing and running performance tests. Recognized bottlenecks and narrowed down the major areas to focus on to bridge this gap. Designed solutions for these problems and iteratively released improvements to get Appian's ML platform closer to the required SLOs.
Solved numerous customer incidents within the set SLAs and ensured that the customer's confidence in Appian's AI capabilities is not degraded.

DynamoDBS3SagemakerSQSKubernetesMachine Learning+1

Software Engineer

Sep 2021 – Oct 2022 · 1 yr 1 mo · McLean, Virginia, United States

- Improved Appian's document extraction capabilities by switching from a native OCR model to AWS Textract to support use cases like skewed, handwritten and noisy text.

Black knight

2 roles

Software Engineer

Jan 2021 – Sep 2021 · 8 mos · Philadelphia, Pennsylvania, United States

Developed micro-services in Java and Python for a virtual assistant that processes mortgage documents by following agile and test driven development practices.
Enhanced an end to end system that redacted NPI information to support documents irrespective of their rotation and orientation.
Incorporated multi-threading to speed up services resulting in performance improvement of 35%

JavaPythonSoftware Development

Software Engineer Intern

May 2020 – Aug 2020 · 3 mos · Philadelphia, Pennsylvania, United States

Worked on an AWS based application that performs OCR, Classification and Extraction on mortgage documents. Translated data obtained from OCR and stored it in S3 which is consumed by the front-end.
Combined documents into packages based on configuration specified by customers.
Restructured data extraction entities of AWS Neptune and wrote queries for it using Gremlin to facilitate tracking of production failures to a specific entity.
Deprecated calls to older services, thereby reducing repeated production failures.

AWSOCRGremlinCloud Computing