Candidates must meet all of the following:
Strong, in-depth Java expertise, including:
JVM internals, concurrency, memory management
Spring / Spring Boot or equivalent enterprise frameworks
Professional Python experience, particularly for backend services, scripting, or AI-related integrations
Hands-on experience with Graph Databases, such as:
Neo4j, Amazon Neptune, JanusGraph, TigerGraph, or similar
Graph data modeling and query languages (e.g., Cypher, Gremlin, SPARQL)
Proven experience integrating custom Agentic AI solutions into enterprise applications, including:
Autonomous or semi-autonomous agents
Tool-using or workflow-oriented AI agents
Production integration, not just experimentation or prototypes
Solid understanding of enterprise application architecture, RESTful APIs, and system integration patterns
Experience working with relational databases and modern persistence layers
Strong problem-solving skills and ability to work with complex domains
The following are not required, but will be considered a strong advantage:
Experience with agentic SDLC tools and processes, such as:
AI-assisted development workflows
Agent-driven testing, code generation, or requirement analysis
Familiarity with microservices architectures and distributed systems
Experience with containerization (Docker, Kubernetes) and cloud platforms (AWS)
