VBest Software Inc
Java Developer with Agentic AI
Skills
2 months ago
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Important information
Contract type:
Freelance / Contract
Salary:
$140,000 – $150,000 / year
Location:
New York, NY, USA
Work mode:
Onsite
Published on:
17 August 2026
What they need
Tasks
Skills required - Java, AWS preferred, Kubernetes, some streaming/Kafka,
NOSQL, CI/CD, testing, alerts, and monitoring(Splunk/dynatrace).
Must know AI for code optimization to accelerate development.
Locations: NYC NY/ Jersey City NJ
W2 Candidates only
Only locals
Requirements
Skills required - Java, AWS preferred, Kubernetes, some streaming/Kafka,
NOSQL, CI/CD, testing, alerts, and monitoring(Splunk/dynatrace).
Must know AI for code optimization to accelerate development.
- Develops secure and high-quality production code, and reviews and debugs code written by others
- Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
- Drives decisions that influence the product design, application functionality, and technical operations and processes
- Serves as a function-wide subject matter expert in one or more areas of focus
- Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
- Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
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