Java Full-Stack AI engineer

Overview

ECS is seeking a Java Full-Stack AI Engineer to work in our Memphis, TN office (Remote Considered).

ECS is seeking a highly skilled and motivated Java Full-Stack AI Engineer to support our USPS client. The candidate will enhance enterprise services and solutions for USPS, as part of an integrated evaluation, integration, strategy, design, implementation, and operational maintenance program. Participates in the design, development, and implementation of software engineering activities. Responsible for the development of components of many analytical tasks and activities.

Establishes input/output processes and defining parameters for interfacing with external production systems and the implementation of system design. Must be able to provide and communicate technology solutions across technical, managerial and customer audiences. Responsible for the resolution process for problems where troubleshooting requires an in-depth understanding and evaluation of system processes. Exercises judgment through understanding of software engineering best practices in selecting methods, techniques, and evaluation criterion for obtaining results.

This role bridges traditional applications with modern AI-driven data workflows, ensuring our systems are scalable, secure, and ready for intelligent automation. As this role will involve supporting rapidly evolving AI/ML projects and use cases, the candidate must have experience in any of the following areas: NLP, data provenance, LLMs/RAG, or deep learning.

• Design, develop and implement web-based applications.
• Design, develop and implement highly complex applications utilizing Oracle and Java technologies.
• Demonstrate strong troubleshooting skills to solve complex problems across a large enterprise.
• Demonstrate a flexible attitude, ability to perform under pressure and ability to handle change easily while meeting deadlines.
• Communicate with technical and non-technical audiences verbally and in writing to design efficient and effective applications.
• Work independently and in a team environment, to give and receive direction.
• Develop and revise Java source code based on clearly defined requirements.
• Experience in designing, architecting, and building Kafka based solutions.
• Extensive experience with messaging and stream processing on Kafka.
• Participate in code reviews for team members as well as yourself.
• Assist in the setup of production environments including application servers and database structure.
• Assist in the implementation of applications through various testing phases and into production environments.
• Must be able to communicate effectively, work in a team environment and think analytically.
• Perform maintenance on programs currently in production.
• Assist QA teams with writing test scripts and explaining functionality.
• Unit Testing candidate releases.
• Collaborate with other departments to ensure high availability and performance.
• Partner with data scientists, data architects, and federal stakeholders to deploy AI/ML models in production.

• Master’s Degree in Computer Science, Engineering, Mathematics, Business Management or equivalent.
• Must be US citizen or Green Card Holder per contract and must be able to obtain a Public Trust clearance
• 12+ years of general experience in information systems, including 7 years of specialized experience providing state-of-the-art solutions in information systems technology
• 5+ years of experience with web technologies (HTML, CSS, JavaScript frameworks)
• 5+ years of experience with Java server technologies (JEE, Spring Framework, Spring Boot)
• 3+ years of experience with SQL and PL/SQL on Oracle or similar platform
• 5+ years of experience with IBM MQ and stream processing on Kafka.
• Expertise in troubleshooting, performance tuning, and query optimization.
• Excellent communication, problem-solving, and organizational skills.
• Ability to work independently and as part of a team.
• Experience with Large Language Models, NLP, GenAI, and scaling of AI tools
• Work comfortably in version control systems (e.g., Git)
• Partner with data scientists, data architects, and federal stakeholders to deploy AI/ML models in production