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• Strong Java developer with very good understanding of micro services.
• Grasp of software engineering skills in modular design, data structures, algorithms
• Deep knowledge and hands on experience with modern applications like spring boot, Angular.
• Experience building and operating critical production systems
• Solid understanding of modern API design and Restful principles
• Fluent with git (preferred) or other SCM system
• Write well designed and testable code
• Strong Experience in automation and build tools like Maven, Ant and Gradle.
• Bachelor's degree in computer science engineering or a related discipline, or equivalent work experience.
• Experience in software development design and implementation of large scale distributed systems and web services building complex software that is testable and designed for extensibility.
• Good understanding of building, deploying, and maintaining critical applications in a cloud based environment.
• Work extensively with open source software capable to modify or extend code maintained as part of an open source project.
• Employ both Object Orientated development skills and Systems Engineering skills.
• Skills Required :  Java,  Spring Boot, Microservices,  Rest API, PCF ,  Oracle PostgreSQL, Jenkins, Kafka 

Role : Gen AI ML Engineer  [Please look for local profiles]
Location : NY [Onsite]
Client : PayPal
Job Description: We are seeking a talented Machine Learning Engineer with expertise in Machine Learning and software engineering to join our team. As a Machine Learning Engineer, your primary responsibility will be to develop Machine Learning (ML) solutions that focus on technology improvements. Specifically, you will be working on projects involving ML & Generative AI solutions for Technology & Data Management Efficiencies such as AI Agents for optimal cloud comptuting, knowledge bots, Assistants etc
Responsibilities: - Collaborate with cross-functional teams such as Data Scientists, Product Partners and Partner Team Developers to identify oppurtunities for process improvements that can be solved using machine learning and generative AI. - Write clean, high-performance, high-quality, maintainable code. - Discovering, analyzing, structuring and mining data. - Define and build innovate ML and Generative AI systems.   - Design and develop ML Engineering Solutions & generative AI Applications for above ensuring scalability, efficiency, and maintainability of such solutions. - Implement prompt engineering techniques to fine-tune and enhance LLMs for better performance and application-specific needs. - Stay abreast of the latest advancements in the field of Generative AI and actively contribute to the research and development of new ML & Generative AI Solutions.
Requirements: - A Master's or Ph.D. degree in Computer Science or a related field. - Minimum 8 years of experience in Machine Learning and last 1-2 years in Generative AI solutions. - Proven experience working as a Full Stack ML Engineer, with a focus on Machine Learning, ML Engineering and experience in Generative AI Applications such as RAG based AI Agents.  - Strong proficiency in programming languages such as Machine Learning Algorithms, Python, Hadoop & Spark etc - Solid knowledge of software engineering best practices, including version control systems (e.g., Git), code reviews, and testing methodologies. - Experience with large language models (LLMs) & prompt engineering techniques, vector DB's ( Mandatory ) - Experience working with various Embedddings /Embedding Models & fine-tuning LLM's ( Nice to have ). - Strong communication skills to effectively collaborate and present findings to both technical and non-technical stakeholders. - Proven ability to adapt and learn new technologies and frameworks quickly. - A proactive mindset with a passion for continuous learning and research in the field of Generative AI.

Role : Gen AI ML Engineer Lead or Architect  [Please look for local profiles]
Location : NY [Onsite]
Client : PayPal

Job Description: We are seeking a talented Generative AI Technical Lead with both DataScience and Software Engineering background to drive development and adoption of AI Solutions. In this role you will contribute to architecting, designing and leading small team of GenAI ML Engineers to build multi agent framework. Your primary responsibility will be to lead development of Generative AI solutions that focus on technology improvements such as Technology Assistants & Data Agents.
Responsibilities: - Collaborate with cross-functional teams such as User Teams, Data Scientists, Core Development Team and Partner Team Developers to identify requirements and architect and lead the development and testing of the AI Agents.  - Design and develop Engineering Solutions & generative AI Applications for above ensuring scalability, efficiency, and maintainability of such solutions. - Assit for Product Roadmap creation & define product requirements. - Architect and Design a large enterprise scale framework such as Knowledge Graph.  - Write clean, high-performance, high-quality, maintainable code. - Design & Implement large scale Clustering, Topic Management system. - Implement prompt engineering techniques to fine-tune and enhance LLMs for better performance and application-specific needs. - Stay abreast of the latest advancements in the field of Generative AI Application Development and actively contribute to the research and development of new Generative AI Applications.
Requirements: - A Master's or Ph.D. degree in Computer Science or a related field. - Minimum 10 years experience with atleast 5 years in designing and building ML/AI Solutions. - Proven experience working in a large Technology Startup or AI Software Product leading development and adoption of the product or a platform.  - Strong proficiency in programming languages such as Java, Python, ML Platorms, LLMs, Machine Learning etc  - Experience in building Graph based systems.  - Experience architecting & leading development of large Generative AI system or platform.  - Experience in development of technical product or platform for large enterprises. - Solid knowledge of software engineering best practices, including version control systems (e.g., Git), code reviews, and testing methodologies. - Experience with large language models (LLMs) & prompt engineering techniques, vector DB's ( Nice to have ) - Strong communication skills to effectively collaborate and present findings to both technical and non-technical stakeholders. - Proven ability to adapt and learn new technologies and frameworks quickly. - A proactive mindset with a passion for continuous learning and research.

• Design and Development: Develop and maintain tools and libraries for GraphQL API creation and management using JavaScript and TypeScript.
• Documentation: Create and maintain guides and best practices for schema design as well as GraphQL API implementation and consumption.
• Governance: Establish and maintain processes for schema change control, breaking change detection, and error sanitization.
• Standardization: Update and publish GraphQL schema and security standards, including application security configurations.
• Security: Implement authentication and authorization mechanisms, input validation, operation complexity limiting, and parser attack protection.
• Build Process: Enhance the GraphQL schema build process with example repositories, automation, and alignment with pipelines.
• Deployment Automation: Improve and automate GraphQL API deployment processes.
• Performance Monitoring: Create and maintain systems for monitoring error rates, latency metrics, and field usage.
• Operational Support: Provide support for all operational aspects to ensure the reliability of GraphQL services.
• Schema Management: Implement and manage a schema registry, ensuring seamless schema proposals, changes, and version control.
• Client Management: Develop features for client identification, caching, and operation registry.
• Collaboration: Work closely with other engineers, product managers, and stakeholders to define and prioritize features and improvements.

• JavaScript and TypeScript: Proficiency in vanilla JavaScript and TypeScript is essential.
• GraphQL: In-depth understanding of GraphQL, including schema design, query optimization, and security best practices.
• Infrastructure Tools: Experience with building and maintaining infrastructure tools and platforms.
• Version Control: Proficiency with Git and experience managing code in a collaborative environment.
• Testing: Experience with unit testing, integration testing, and end-to-end testing frameworks.
• Problem Solving: Strong analytical and problem-solving skills with a focus on performance optimization and scalability.
• Communication: Excellent communication skills and the ability to work effectively in a team environment.

• ESLint: Proficiency with ESLint for maintaining code quality and consistency.
• Rust: Experience with Rust programming language.
• DevOps: Familiarity with CI/CD pipelines, containerization (Docker), and orchestration tools (Kubernetes).
• Cloud Services: Experience with cloud platforms such as AWS, Google Cloud, or Azure.
• Monitoring Tools: Familiarity with monitoring and logging tools like Datadog and OpenTelemetry.

• Experience: Minimum of 3 years of experience in software development, with a focus on GraphQL and infrastructure tools.

• Design and Development: Develop and maintain tools and libraries for REST and GraphQL API creation and management using vanilla JavaScript, TypeScript and NodeJS.
• Standardization: Update and publish REST and GraphQL API schema and security standards, including application security configurations.
• Collaboration: Work closely with other engineers, product managers, and stakeholders to define and prioritize features and improvements.

• NodeJS and Typescript: Excellent skills with NodeJS ecosystem. Experience with creating node modules using vanilla JS and TypeScript and publishing them. Good understanding of package managers like NPM and Webpack
• Testing: Experience with unit testing, integration testing, and end-to-end testing frameworks. Proficient in writing unit tests and functional tests using Jest or similar libraries.
• Infrastructure Tools: Understanding of Service Oriented Architecture (SOA) to aid in debugging. Relevant technologies: Postman, cURL, Swagger, OpenAPI, Datadog
• Continuous Integration Tools: Familiarity with CI tools like Jenkins, Harness, GitHub Actions, or similar tools to set up custom pipelines.
• Version Control: Proficiency with Git and experience managing code in a collaborative environment.
• Communication: Excellent communication skills and the ability to work effectively in a team environment.

• Spectral: Proficiency with adding custom rules in Spectral CLI
• ESLint: Proficiency in ESLint, including the ability to write custom ESLint rules
• Cloud Services: Experience with cloud platforms such as AWS, Google Cloud, or Azure.
• Monitoring Tools: Familiarity with monitoring and logging tools like Datadog and OpenTelemetry.

• Experience: Minimum of 3 years of experience in software development, with a focus on NodeJS, Typescript and infrastructure tools.

Thanks,