Senior Java with AI Experience

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. 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.

Project Description

Digital Technology team designs, develops, and maintains massively scaling technology solutions brought to life with innovative architectures, data analytics, digital solutions, and practical AI-enabled capabilities. The Notifications team enables enterprise communication capabilities supporting customer and crew portfolios. This contractor role will focus on hands-on design, development, modernization, and production delivery of notification platform services, integrations, event-driven capabilities, and AI-enabled communication use cases.

Responsibilities

• The role of Senior Developer will have a technical focus on enabling Notifications at the enterprise level and supporting a robust communication platform for customer and crew portfolios. This is a hands-on senior individual contributor role, not a management role. The expectation is to actively design, code, debug, optimize, deploy, and support production-grade solutions.
• 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.

Skills – 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.

Preferred Qualifications:

• Experience designing and developing enterprise notification, communication, customer messaging, content management, or eventing platform solutions.
• Experience with Twilio or similar communication/messaging platforms.
• Experience applying AI to communication use cases such as personalization, routing, prioritization, content quality checks, template assistance, intent classification, summarization, or operational anomaly detection.
• Experience with AI observability, LLMOps/MLOps practices, model/prompt evaluation, AI guardrails, and production monitoring of AI-enabled features.
• AWS certification or equivalent cloud certification.
• Experience in high-scale, 24x7 production environments.

Nice to Have

• Airline, travel, customer platforms, or crew operations domain experience.