AI Engineer | Java & AWS Bedrock, SageMaker & RAG

Job Summary

Synechron seeks an experienced AI Engineer to design, build, and operationalize AI-powered solutions that integrate with Java/Spring Boot backends on AWS. This role combines ML/AI capability with cloud infrastructure, data pipelines, and front-end touchpoints to deliver scalable, secure, and business-ready solutions. The ideal candidate will own end-to-end implementation—from models and embeddings to production-grade services and integrations with enterprise tooling.

Software Requirements Essential AWS Bedrock, Claude, Titan embeddings, and Guardrails experience RAG architecture using Sage. Maker and Lambda, including embedding pipelines and chunking strategies Vector databases: Open. Search or Aurora PostgreSQL (pgvector) Graph database: Amazon Neptune Orchestration: AWS Step Functions MCP tool integrations (Jira, Service.

Now, q. Test, etc.) Backend development with Java/Spring Boot (integration-focused) Frontend exposure: Angular (basic proficiency) AWS infrastructure: ECS Fargate, Event. Bridge, API Gateway, IAM, Secrets Manager, S3 Strong programming capabilities in Java and experience applying AI/ML results in production apps Preferred Deepen knowledge across additional AWS AI services and security best practices Experience with scalable data engineering pipelines and model deployment automation Overall Responsibilities 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: Open.

Search 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, Sage. Maker, Lambda, Step Functions, ECS/Fargate, Event. Bridge, 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/Net.

Beans), Agile/Scrum methodologies Preferred: MCP tool integrations (Jira, Service. Now, q. Test), 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, Sage.

Maker, Lambda, Step Functions, and related services Integrating with MCP tools and enterprise workflows (Jira, Service. Now, q. Test) 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 Professional Competencies Critical Thinking & Problem Solving: Analyzes complex problems and designs scalable AI-enabled solutions Leadership & Teamwork: Collaborates across teams, mentors peers, and drives technical discussions Communication & Stakeholder Management: Clear, concise communication with technical and non-technical stakeholders Adaptability & Learning Orientation: Demonstrates flexibility to adopt new tools and approaches Innovation Mindset: Seeks opportunities to improve performance, reliability, and user value Time & Priority Management: Manages multiple streams, sets priorities, and meets deadlines S​ YNECHRON’S DIVERSITY & INCLUSION STATEMENT Diversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer.

Our Diversity, Equity, and Inclusion (DEI) initiative ‘Same Difference’ is committed to fostering an inclusive culture – promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply.

We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more. All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant’s gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law .

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