JAVA AI Engineer:
JAVA AI Engineer:
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Job Description
- Lead software architecture and component design, align solutions with business goals across the full delivery lifecycle.
- Drive AI-assisted engineering by select, standardise, and govern AI tool to improve productivity, quality, and compliance.
- Provide technical troubleshooting and performance optimisation, resolve system issue and coordinate incident across team.
- Collaborate across agile team to guide solution design, estimation, and requirement refinement.
- Identify and manage risk, proactively surface issue that may impact delivery or project success.
- Promote innovation and R&D by evaluate new technology, build business case, and enhance solution capability.
- Ensure engineering excellence through code review, quality assurance (including AI-generated code), team capability development, ethical AI practice, and cyber risk management.
- Demonstrate strong understanding of DevSecOps practices, benchmarks, and performance measurement.
- Deliver full-stack development across Java/J2EE, Spring Boot, and Angular, building scalable microservices and web applications.
- Design secure, scalable, and maintainable solutions using MVC patterns, modular architecture, and dependency injection.
- Integrate systems and manage APIs, including databases, third-party services, and secure authentication (OAuth2, JWT).
- Apply advanced AI engineering skills, including prompt engineering, context assembly (RAG), and automated quality/compliance controls.
- Drive DevOps, automation, and cloud adoption, including CI/CD pipelines, testing frameworks, containers, and Kubernetes/OpenShift.
- Provide technical leadership and governance, covering AI risk, security (including LLM threats), regulatory compliance, stakeholder communication, and delivery within financial services environments.
- A passion for leveraging emerging technologies to stay ahead in a rapidly evolving digital landscape.
- JAVA AI Engineer:
- Lead software architecture and component design, align solutions with business goals across the full delivery lifecycle.
- Drive AI-assisted engineering by select, standardise, and govern AI tool to improve productivity, quality, and compliance.
- Provide technical troubleshooting and performance optimisation, resolve system issue and coordinate incident across team.
- Collaborate across agile team to guide solution design, estimation, and requirement refinement.
- Identify and manage risk, proactively surface issue that may impact delivery or project success.
- Promote innovation and R&D by evaluate new technology, build business case, and enhance solution capability.
- Ensure engineering excellence through code review, quality assurance (including AI-generated code), team capability development, ethical AI practice, and cyber risk management.
- Demonstrate strong understanding of DevSecOps practices, benchmarks, and performance measurement.
- Deliver full-stack development across Java/J2EE, Spring Boot, and Angular, building scalable microservices and web applications.
- Design secure, scalable, and maintainable solutions using MVC patterns, modular architecture, and dependency injection.
- Integrate systems and manage APIs, including databases, third-party services, and secure authentication (OAuth2, JWT).
- Apply advanced AI engineering skills, including prompt engineering, context assembly (RAG), and automated quality/compliance controls.
- Drive DevOps, automation, and cloud adoption, including CI/CD pipelines, testing frameworks, containers, and Kubernetes/OpenShift.
- Provide technical leadership and governance, covering AI risk, security (including LLM threats), regulatory compliance, stakeholder communication, and delivery within financial services environments.
- A passion for leveraging emerging technologies to stay ahead in a rapidly evolving digital landscape.
More Info
Key Skills
automated quality compliance controls
cloud adoption
AI engineering
MVC patterns
DevSecOps practices
context assembly
prompt engineering
modular architecture
RAG
Containers
About Company
Skills:
Java, Hibernate, Maven, Kafka, Sql, Redis, Angular, Jenkins, React, Spring Framework, Gradle, Javascript, Spring Core, Restful Apis, Oracle, Devops Tools, Cloud platforms, Microservices architecture, GitHub Actions, Java 8 or later, CI/CD
Skills:
Core Java, Microservices, Database JDBC Integration, Backend Engineering Fundamentals, AI LLM-powered Features
Skills:
Java, Spring Boot, Kafka, Mongo Db, Sql, Microservices, AWS, Cockroach DB, FID setup, AI Development Certification, GKP instance setup, NoSQL Databases, Jules
Skills:
Agile Methodologies, Debugging, Testing, System Design, Cloud Technologies, Software Development Life Cycle, Application Development, software engineering concepts, CI/CD, modern programming languages, front-end technologies, enterprise-authorized AI-assisted software development tools, Security, Application Resiliency, operational stability, database querying languages