Abhishek D.

Software Engineer

United States8 yrs 9 mos experience

AI ML PractitionerHighly Stable

Key Highlights

Expert in test automation with ML capabilities.
Pioneered security testing in CI/CD pipelines.
Strong background in cloud computing and data analytics.

Stackforce AI infers this person is a SaaS expert with a focus on test automation and cloud solutions.

Contact

thinkdifferent30@gmail.com LinkedIn

Skills

Core Skills

Test AutomationCloud ComputingSecurity TestingMachine LearningData Analytics

Other Skills

AWSAgile MethodologiesAmazon Web Services (AWS)Business AnalysisCI/CDConsultingContinuous Integration (CI)CypressDeep LearningFeature EngineeringGenerative AIGitGoogle Cloud Platform (GCP)JBoss Application ServerJava

About

We're shaping the future of software delivery with cutting-edge frameworks for UI and backend systems, underpinned by a seamless CI/CD pipeline leveraging Jenkins and Docker. Our team's commitment to efficiency is mirrored in our daily transparent reporting, which underscores the robustness of our deployment practices. My educational foundation in Information Technology, paired with a Master's in Computer Science, complements my proficiency in Agile methodologies and Amazon EKS. We've fostered a nurturing environment for team growth, with my role as a mentor reinforcing our collective success. With a recent addition in Gen AI and deep learning I am embedding AI innovation into our software solutions.

Experience

8 yrs 9 mos

Total Experience

7 yrs

Average Tenure

2 yrs 2 mos

Current Experience

Seabourn cruise line

Lead Engineer

Apr 2024 – Present · 2 yrs 2 mos · Seattle, Washington, United States · Hybrid

Xebia

Architect

Sep 2017 – Sep 2024 · 7 yrs · Seattle, Washington, United States · On-site

Revolutionized test automation by creating Python-based framework with ML capabilities that predicts potential failure points with 89% accuracy
Established "Shift-Left" testing culture across engineering teams, reducing defect discovery time by 72% and cutting development costs by $1.2M annually
Pioneered implementation of security testing within CI/CD pipeline, uncovering 23 critical vulnerabilities before production release
Architected comprehensive cloud testbed environments in AWS that simulate real-world conditions for testing distributed microservices architecture
Developed PyTorch-based anomaly detection system that automatically identifies security and performance regressions in test data
Implemented test data analytics platform providing actionable quality metrics to executive leadership, driving strategic product improvements

PythonMachine LearningTest AutomationSecurity TestingCloud ComputingData Analytics