Java Backend Engineer – Agentic Worflows

Job Summary

We are seeking a highly skilled Java Backend Engineer with expertise in agentic workflows and MCP (Model Context Protocol) service integration to join our engineering team. The ideal candidate will design develop and optimize backend systems that power intelligent autonomous agents and context-driven services. You will collaborate with cross-functional teams to architect scalable solutions that leverage cutting-edge AI workflows while maintaining reliability performance and security.

Location: Austin TX

Years of experience needed

Minimum 7 years of experience in Java Backend development exposure to Agentic workflows

Required skills:

• Bachelors masters degree in computer science Engineering or related field.
• 5 years of backend engineering experience with strong expertise in Java (Java 11 PLUS) and Python.
• Proven experience with agentic workflows (autonomous task orchestration tool use context-driven execution).
• Hands-on with MCP (Model Context Protocol) service development and integration.
• Strong understanding of microservices architecture RESTful APIs gRPC and message queues (Kafka RabbitMQ etc.).
• Experience with databases (SQL and NoSQL) and caching solutions (Redis Memcached).
• Familiarity with cloud platforms (AWS GCP or Azure) and containerization (Docker Kubernetes).
• Solid grasp of concurrency multithreading and distributed systems design.
• Proficiency in CI/CD pipelines testing frameworks (JUnit Mockito) and code quality tools.
• Excellent problem-solving debugging and communication skills

Responsibilities

• Design develop and maintain scalable Java-based backend services to support agentic workflows and AI-driven applications.
• Implement and optimize MCP services to enable seamless context sharing and dynamic orchestration between models agents and tools.
• Architect APIs microservices and event-driven systems that ensure high performance reliability and low-latency communication.
• Collaborate with data scientists AI ML engineers and frontend developers to integrate agentic intelligence into production systems.
• Write clean maintainable and testable code while following best practices in software engineering.
• Monitor troubleshoot and optimize system performance scalability and fault-tolerance.
• Contribute to workflow automation context management and intelligent decision-making systems.
• Stay up to date with emerging technologies in AI distributed systems and backend engineering

Preferred Qualification:

• Experience with AI ML infrastructure LLM-based applications or agent frameworks.
• Knowledge of event sourcing CQRS and workflow engines (e.g. Temporal Camunda Airflow).
• Contributions to open-source projects related to agentic systems or MCP.
• Understanding of observability (logging tracing metrics) in distributed systems.

Behavioral Skills:

• Excellent Communication skills and collaboration skills
• Ability to propose and implement improvements in the system
• Ability to work with cross-functional stakeholders