• Implement and maintain complex Linux-based environments • Manage and optimize virtual environments (KVM) and container platforms (Podman) • Ensure system security and compliance, including SELinux configuration and troubleshooting • Develop and maintain CI/CD pipelines using tools such as Jenkins • Automate operational and deployment tasks using Python and Bash • Collaborate with development and infrastructure teams to improve system reliability and efficiency • Support troubleshooting, performance tuning, and system optimization

• Develop and maintain EAG/API-gateway automation components that integrate with Government-approved CI/CD pipelines. • Create and validate configuration-as-code, pipeline-compatible deployment artifacts, gateway promotion workflows, API validation gates, and migration automation components. • Support automated checks for API specification quality, governance compliance, Zero Trust controls, telemetry, configuration drift, and production-readiness evidence. • Build automation and validation evidence that supports PWS automation outcomes, including 75 percent manual onboarding reduction, 90 percent automated onboarding success rate, and 100 percent Zero Trust/governance compliance prior to production deployment. • Troubleshoot gateway-side CI/CD integration issues, including deployment failures, configuration errors, credential/certificate dependencies, environment promotion issues, and validation gate failures. • Support Git-based version control, branching, pull/merge request workflows, artifact repositories, and release evidence. • Coordinate with Government CI/CD, DevSecOps, cybersecurity, identity, network, and release teams for platform-owned dependencies. • Produce pipeline documentation, automation runbooks, validation logs, deployment evidence, rollback steps, and knowledge-transfer materials.

• Design, develop, and maintain automated test frameworks for UI, API, and backend testing. • Lead the automation strategy, prioritizing efforts based on risk, impact, and business needs; establish and enforce automation standards and best practices. • Convert manual test cases into automated solutions. • Integrate automated tests into CI/CD pipelines. • Execute, monitor, and maintain automated regression and smoke test suites to ensure product stability and quality. • Conduct root cause analysis on defects and test failures. • Prepare and communicate quality metrics and status reports to management. • Collaborate with Product Owners, Business Analysts, Developers, and other stakeholders to ensure quality requirements are clearly defined.

• Design, build, and maintain scalable data pipelines for ingesting, processing, and enriching large datasets. • Develop Python-based automation for data collection, transformation, validation, and workflow orchestration. • Build and optimize data processing workflows using Databricks, PySpark, SQL, and Delta Lake. • Integrate and process data from multiple SaaS platforms through REST APIs and other integrations. • Develop scalable workflows for lead generation, company and contact enrichment, and sales intelligence. • Implement processes for data cleansing, deduplication, entity resolution, normalization, and contact/company matching. • Process structured, semi-structured, and JSON data from a variety of internal and external sources. • Collaborate with product, engineering, and go-to-market teams to translate business requirements into scalable technical solutions. • Identify opportunities to automate repetitive processes and improve operational efficiency. • Continuously evaluate and adopt new AI tools and technologies that improve development speed and data quality.