Java Developer VP (C13)

The Applications Development Technology Lead Analyst is a senior-level position responsible for establishing and implementing new or revised application systems and programs in coordination with the Technology team. The overall objective of this role is to lead application systems analysis and programming activities.

Key Responsibilities

• Lead by example in bringing agility into software development by following Agile best practices.
• Design, develop, and implement Generative AI models, including LLMs, GANs, VAEs, and Diffusion Models, using Python and relevant deep learning frameworks such as TensorFlow and PyTorch.
• Integrate Generative AI capabilities into existing systems and develop new AI-powered applications.
• Serve as a liaison between the development manager and the Scrum team.
• Coach and mentor the team and eliminate impediments.
• Manage stakeholders, partner to develop roadmaps, releases, and milestones, and remain accountable for delivery.
• Develop frameworks, designs, data models, architecture diagrams, and related documentation, and communicate them within and outside the team.
• Ensure the team follows best engineering standards, including DevOps and SRE.
• Serve as the second-level reviewer for application design and implementation.
• Provide input and review test plans and test cases for adequate coverage to ensure product quality.
• Be accountable for smooth releases.
• Serve as the single point of contact for production incidents at the L3 level; troubleshoot, perform root cause analysis, and resolve issues permanently.
• Ensure sprint deliverables are met.
• Adjust team capacity while remaining hands-on in addressing stories as a developer.

Required Qualifications

• 10+ years of Full Stack software engineering experience developing enterprise-scale applications.
• Expertise in building web applications using the Java, Springboot, Microservices, Angular/React, and Oracle/PostgreSQL technology stack.
• Proven experience with Generative AI models, including hands-on experience with large language models (LLMs) or other generative architectures.
• Proficiency in deep learning frameworks such as TensorFlow, PyTorch, or JAX.
• Experience with Google ADK or similar Google AI/ML platforms and SDKs.
• Expertise in enterprise integrations through RESTful APIs, Kafka messaging, and related technologies.
• Expertise in Elastic Search, NoSQL databases, and caching solutions.
• Expertise in designing and optimizing software solutions for performance and stability.
• Expertise in troubleshooting and problem-solving.
• Expertise in Site Reliability Engineering.
• Expertise in Test-Driven Development.
• Expertise in Authentication, Authorization, and Security.
• Familiarity with AWS cloud and preparation to migrate applications, services, and data to AWS.