Software Development Engineer

Gaurav Anil Haral

201-***-**** *************@*****.*** LinkedIn

PROFESSIONAL SUMMARY

Technically adept and impact-focused engineer with a demonstrated aptitude for architecting scalable backend infrastructures, designing API-driven systems, and orchestrating real-time data pipelines within resilient cloud-native ecosystems. Proficient in Python, Java, AWS, and distributed systems, with practical experience operationalizing machine learning solutions in production contexts. Recognized for intellectual agility, a propensity for rapid skill acquisition, and the ability to leverage emerging technologies to deliver strategic, high-value outcomes. TECHNICAL SKILLS

Languages: Python, Java, SQL, Go, C++

Backend & Frameworks: FastAPI, Django, Flask, Spring Boot, REST APIs, Microservices, Pydantic Cloud & DevOps: AWS, Azure, Docker, Kubernetes, Terraform, Jenkins, GitLab CI/CD Data & ML Tools: Kafka, Kinesis, Pandas, Scikit-learn, PyTorch, MLflow, Jupyter, Airflow Monitoring & Observability: ELK Stack, Prometheus, Grafana, CloudWatch, PagerDuty Visualization & Reporting: Tableau, Matplotlib, Seaborn Certifications: AWS Cloud Practitioner, IBM Data Science, ISO Certified C++ Programmer WORK EXPERIENCE

Systems Software Engineer, PDA, New Jersey July 2024 – September 2025

• Directed modernization of a healthcare platform used by over 200 practices with 200,000 annual visits, addressing

• frequent Migrated downtime core systems and scaling to AWS limitations and Azure caused including by outdated EC2, Lambda, on-premises RDS, infrastructure. and S3, which improved scalability and

• eliminated Designed secure latency APIs bottlenecks to integrate while EHR enabling systems real-financial time access platforms to critical to automate patient revenue data. cycle processes, reduce billing errors, and improve data consistency. Additionally, built a unified patient portal using React, Next.js, and Flask to

• support Developed appointment real-time data scheduling, pipelines payments, using Kafka, and access Kinesis, to and medical Python records. to process clinical notes, detect billing anomalies,

• and Created trigger operational machine dashboards learning workflows using Python, for scheduling SQL, and optimization. Tableau to visualize KPIs that supported data-driven decisions

• on Implemented staffing, patient security flow, protocols and revenue using performance. OAuth 2.0, JWT, and SAML SCIM with RBAC and audit logging to ensure Software HIPAA-Development compliant, multi-Engineer tenant II, access Lightcast, control New across York all services. June 2022 – June 2024

• Developed scalable backend systems with Java, and Python (Django, Fast API), achieving 99.99 percent uptime and 50ms average response time for high-traffic Job posting APIs.

• Engineered RESTful APIs and microservices adhering to SOLID principles, resulting in a 40 percent reduction in system complexity. Leveraged terraform & CloudFormation for infrastructure provisioning, optimized deployments with docker and CI/CD pipelines.

• Created a custom logging and monitoring solution using ELK stack, enabling real-time issue detection and reducing MTTR from hours to minutes.

• Supported PostgreSQL schema optimization and analytics queries for reporting pipelines and data integrations.

• Contributed to all elements of SDLC including design, coding, code review, unit testing, bug fixing, and operations.

• Mentored junior developers through code reviews, pair programming, and technical guidance on architectural decisions.

• Collaborated with product manager, principal staff software engineer, and teammates to lead epic and sprint planning sessions, ensuring seamless alignment of deliverables with interdependent teams and managing dependencies on other teams’ outputs.

Research Assistant, Pace University, New York June 2021 – June 2022

• Conducted research in NLP, and cybersecurity, including model evaluation, deep learning experiments, and data preprocessing. Built ML models for anomaly detection using Python, scikit-learn, PyTorch, and implemented reproducible pipelines using Git versioning.

• Performed literature reviews and co-authored technical research on emerging AI trends and network security.

• Maintained Linux-based research lab infrastructure and assisted with workshops on AI, ML, and cloud development. Software Development Engineer, Kaizen Software Services, IN May 2017 – June 2020

• Built and maintained backend APIs using Java, Python, Flask, and React.js for enterprise clients across finance, retail, and logistics domain.

• Developed caching mechanisms using hash tables and LRU strategies to improve performance & reduce backend load.

• Managed CI/CD pipelines using GitLab to automate builds, tests, and deployments, reinforcing best practices in production workflows.

• Containerized applications with Docker and supported deployments in AWS and Azure environments, gaining early experience in cloud-native development.

EDUCATION

Master of Science in Computer Science,

Pace University, New York, NY

Concentration: Backend Development and Artificial Intelligence Awards: Dean’s Scholar Award

Bachelor of Mechanical Engineering,

Pune University, Maharashtra, IN

Honors: First Class with Distinction

Contact this candidate