Senior Java Software Engineer

Your Impact

• Design and build scalable Java and Spring Boot services that modernize interactions between existing applications and PostgreSQL.
• Implement production-ready data access and integration components using Spring JDBC, Hibernate, REST APIs, and modern backend engineering patterns.
• Apply AI and RAG capabilities to engineering and platform use cases, including retrieval pipelines, embeddings, vector search, LLM integrations, and AI-assisted access to technical knowledge.
• Explore and evaluate opportunities for generative AI and agentic solutions, balancing accuracy, security, observability, performance, and business value.
• Debug and analyze complex system interactions, message flows, dependencies, and integration points across modern and legacy components.
• Improve performance and resilience through PostgreSQL optimization, appropriate caching with Redis or Caffeine, observability, automated testing, and incremental migration strategies.
• Collaborate with engineers and client stakeholders to communicate design decisions, technical trade-offs, risks, and recommendations.

Qualifications

Skills & Experience

• Strong hands-on experience building production applications with Java and Spring Boot.
• Experience with Spring JDBC and/or Hibernate, including database connectivity, transactions, and connection-pool management.
• Strong knowledge of PostgreSQL or comparable relational databases, including query optimization, indexing, and performance troubleshooting.
• Hands-on experience with Azure and cloud-native engineering practices.
• Practical understanding or hands-on experience with Generative AI, LLMs, or RAG architectures, including concepts such as embeddings, vector databases, retrieval, prompt orchestration, and evaluation.
• Experience building and integrating REST APIs and distributed backend services.
• Familiarity with modern engineering practices including CI/CD, automated testing, observability, debugging, and Infrastructure as Code.
• Strong communication and problem-solving skills, particularly the ability to explain technical decisions and trade-offs clearly to both engineers and client stakeholders.

Set Yourself Apart With

• Experience designing or implementing RAG solutions, AI agents, tool-calling workflows, MCP integrations, or enterprise LLM applications.
• Experience with Azure AI services, vector search, AI application monitoring, or production GenAI architectures.
• Working knowledge of C or C++, particularly experience reading existing codebases, tracing function calls, or modifying integration points.
• Experience modernizing large-scale legacy or enterprise applications through incremental migration rather than full rewrites.
• Experience with Redis, Caffeine, Kafka, or other technologies supporting high-volume distributed systems.
• Exposure to AWS or GCP, or frontend technologies such as Angular or React.