Senior Java with AI Experience
Pozent Corporation · Chicago, IL · 1 wk ago
HybridEngineeringContract
Responsibilities
- Design and implement core services for the enterprise Notifications platform, including APIs, event-driven integrations, orchestration components, templates, and platform capabilities.
- Write, review, debug, and optimize production code actively; lead through hands-on engineering contribution rather than delegation.
- Build cloud-native backend services using Java, Spring Boot, Apache Camel, microservices, container technologies, and AWS services.
- Develop and integrate AI/GenAI capabilities hands-on, including prompt design, LLM integration, RAG pipelines, embeddings/vector search, semantic search, classification, summarization, and AI-assisted communication workflows.
- Prototype, validate, and productionize AI-enabled features while considering latency, accuracy, cost, monitoring, fallback design, and operational reliability.
- Design solutions for high availability, scalability, resiliency, observability, performance, security, privacy, and compliance needs.
- Support integrations with internal enterprise systems, eventing platforms, data providers, communication providers, and vendor-managed services as needed.
- Troubleshoot and resolve complex production issues directly, including performance bottlenecks, integration failures, data issues, and system reliability concerns.
- Work closely with architects, product owners, business stakeholders, development teams, and vendor teams to convert requirements into working solutions.
- Contribute to technical design, system documentation, code reviews, automated testing, CI/CD pipelines, release readiness, and production support practices.
- Ensure solutions are aligned with enterprise engineering standards, security expectations, and application lifecycle best practices.
- Mentor developers through code-level guidance, design reviews, and engineering best practices; however, the primary expectation remains hands-on delivery.
Requirements
- Must Have Bachelor’s degree in Computer Science, Information Systems, Engineering, related field, or equivalent work experience required.
- Minimum 8 years of overall experience in software engineering, application development, integration, and SDLC delivery.
- Strong recent hands-on software development experience; candidate must be comfortable spending the majority of time coding, debugging, designing, and delivering working software.
- Minimum 8 years of hands-on Java backend development experience, including Spring Boot, REST APIs, microservices, and open-source technologies.
- Minimum 3 years of hands-on experience with event-driven systems, messaging, streaming, integration, or notification platform capabilities.
- Hands-on experience with Apache Camel or equivalent enterprise integration frameworks.
- Minimum 4 years of hands-on experience with AWS or equivalent cloud services such as EC2, S3, RDS, VPC, CloudFront, Lambda, EKS, ECS, API Gateway, DynamoDB, DocumentDB, AmazonMQ, or related services.
- Strong hands-on AI/GenAI implementation experience in enterprise or production-grade applications; AI experience should not be limited to strategy, vendor discussions, or conceptual understanding.
- Practical experience personally implementing one or more AI capabilities such as LLM integration, prompt engineering, RAG, embeddings/vector search, semantic search, classification, summarization, AI-assisted workflow automation, or decision-support capabilities.
- Understanding responsible AI and secure AI engineering practices, including data privacy, access control, guardrails, evaluation, monitoring, hallucination risk, human review where needed, and auditability.
- Experience with observability and analytics tools such as Dynatrace, ELK Stack, CloudWatch, or equivalent tools.
- Experience working in agile delivery environments where CI/CD, automated testing, code quality, deployment readiness, and production support are critical.
- Demonstrated knowledge of software engineering best practices such as version control, software packaging, release management, automated testing, secure coding, and operational readiness.
- Strong analytical and problem-solving skills with ability to diagnose complex technical issues independently.
- Must be self-motivated, collaborative, and able to communicate effectively with technical and non-technical stakeholders.
Skills
- Bachelor’s degree in Computer Science, Information Systems, Engineering, related field, or equivalent work experience required.
- Minimum 8 years of overall experience in software engineering, application development, integration, and SDLC delivery.
- Strong recent hands-on software development experience; candidate must be comfortable spending the majority of time coding, debugging, designing, and delivering working software.
- Minimum 8 years of hands-on Java backend development experience, including Spring Boot, REST APIs, microservices, and open-source technologies.
- Minimum 3 years of hands-on experience with event-driven systems, messaging, streaming, integration, or notification platform capabilities.
- Hands-on experience with Apache Camel or equivalent enterprise integration frameworks.
- Minimum 4 years of hands-on experience with AWS or equivalent cloud services such as EC2, S3, RDS, VPC, CloudFront, Lambda, EKS, ECS, API Gateway, DynamoDB, DocumentDB, AmazonMQ, or related services.
- Strong hands-on AI/GenAI implementation experience in enterprise or production-grade applications; AI experience should not be limited to strategy, vendor discussions, or conceptual understanding.
- Practical experience personally implementing one or more AI capabilities such as LLM integration, prompt engineering, RAG, embeddings/vector search, semantic search, classification, summarization, AI-assisted workflow automation, or decision-support capabilities.
- Understanding responsible AI and secure AI engineering practices, including data privacy, access control, guardrails, evaluation, monitoring, hallucination risk, human review where needed, and auditability.
- Experience with observability and analytics tools such as Dynatrace, ELK Stack, CloudWatch, or equivalent tools.
- Experience working in agile delivery environments where CI/CD, automated testing, code quality, deployment readiness, and production support are critical.
- Demonstrated knowledge of software engineering best practices such as version control, software packaging, release management, automated testing, secure coding, and operational readiness.
- Strong analytical and problem-solving skills with ability to diagnose complex technical issues independently.
- Must be self-motivated, collaborative, and able to communicate effectively with technical and non-technical stakeholders.