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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.
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
Qualifications/Required skills:
Bachelor's/Master's degree in Computer Science, Engineering, or related field.
5 years of backend engineering experience with strong expertise in Java (Java 11 ) 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 & NoSQL) and caching solutions (Redis, Memcached).
Familiarity with cloud platforms (AWS, Google Cloud Platform, 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
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
Below Are Top 5 Skills For Candidate Assessment.
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.
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
Qualifications/Required skills:
Bachelor's/Master's degree in Computer Science, Engineering, or related field.
5 years of backend engineering experience with strong expertise in Java (Java 11 ) 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 & NoSQL) and caching solutions (Redis, Memcached).
Familiarity with cloud platforms (AWS, Google Cloud Platform, 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
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
Below Are Top 5 Skills For Candidate Assessment.
- Java (11 ) and Python Backend Development strong coding & microservices experience
- Agentic Workflows orchestration, autonomous task execution, tool use
- MCP (Model Context Protocol) service development & integration
- Distributed Systems & APIs REST/gRPC, event-driven architectures
- Cloud & Containers AWS/Google Cloud Platform/Azure, Docker, Kubernetes