Description

Architect, develop, test, and maintain AI-enabled Java applications and services

Collaborate with cross-functional teams to translate business needs into technical solutions

Design robust data and AI pipelines, embeddings, and retrieval mechanisms for RAG scenarios

Ensure code quality through reviews, testing, and documentation

Stay current with AI/ML and cloud-native trends; advocate for secure, scalable solutions

Integrate with enterprise tools and ensure seamless deployment and monitoring

Promote sustainable and efficient development practices, including cost-aware cloud usage

Technical Skills (By Category)

Programming Languages

Essential: Java

Preferred: Python (for AI/ML workflows and tooling)

Databases/Data Management

Essential: OpenSearch or Aurora PostgreSQL (with pgvector) for vector/search data

Preferred: MySQL, Oracle, SQL Server; data modeling and ORM concepts (e.g., JPA)

Cloud Technologies

Essential: AWS (Bedrock, SageMaker, Lambda, Step Functions, ECS/Fargate, EventBridge, API Gateway, IAM, Secrets Manager, S3)

Preferred: Cost optimization, security controls, multi-AZ/multi-region deployment strategies

Frameworks and Libraries

Essential: Spring Boot, Hibernate/ORM, Struts

Preferred: RESTful APIs, microservices architecture, JPA, AI/ML libraries and tooling

Development Tools and Methodologies

Essential: IDEs (Eclipse/IntelliJ/NetBeans), Agile/Scrum methodologies

Preferred: MCP tool integrations (Jira, ServiceNow, qTest), Git, CI/CD practices, unit testing frameworks (JUnit, Mockito)

Security Protocols

Essential: Secure coding practices, IAM-based access control, Secrets management

Preferred: Secure API design, encryption, authentication/authorization concepts, auditability

Experience Requirements

Years of Experience: 7+ years in software/AI engineering

Domain Experience: AI/ML, RAG implementations, cloud-native architectures, integration with enterprise systems

Industry Experience Preferences: Experience working in cross-functional teams; collaboration with back-end, front-end, and platform teams

Alternative Pathways: Equivalent hands-on experience and demonstrated outcomes may be considered

Day-to-Day Activities

Designing and implementing AI-enabled features within Java/Spring Boot services

Building and maintaining data pipelines, embeddings, and vector search components

Developing with AWS Bedrock, SageMaker, Lambda, Step Functions, and related services

Integrating with MCP tools and enterprise workflows (Jira, ServiceNow, qTest)

Collaborating with frontend engineers (Angular) and QA to ensure end-to-end quality

Performing code reviews, debugging, and performance tuning

Keeping up-to-date with AI/ML and cloud-native innovations

Qualifications

Education: Bachelor's degree in Computer Science, Information Technology, or related field (Master’s preferred)

Certifications (preferred): AWS certification(s) (Solutions Architect/DevOps/ML Specialty) and Java-related credentials

Training: Commitment to ongoing professional development and staying current with industry best practices

Equivalency: Relevant hands-on experience may be considered in place of formal degrees

Key Skills

Education

Bachelor's degree