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 SageMaker and Lambda, including embedding pipelines and chunking strategies
- Vector databases: OpenSearch or Aurora PostgreSQL (pgvector)
- Graph database: Amazon Neptune
- Orchestration: AWS Step Functions
- MCP tool integrations (Jira, ServiceNow, qTest, etc.)
- Backend development with Java/Spring Boot (integration-focused)
- Frontend exposure: Angular (basic proficiency)
- AWS infrastructure: ECS Fargate, EventBridge, 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: 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 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
SYNECHRON’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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