Senior Software Engineer - Java + Agentic AI

We are looking for a highly skilled Senior Software Engineer - Backend to build and scale next-generation AI-powered platforms. The ideal candidate will have strong expertise in Java-based backend development, distributed systems, microservices architecture, and hands-on experience building Agentic AI applications using modern LLM frameworks.

You will work closely with Product, AI/ML, and Engineering teams to design intelligent systems capable of autonomous decision-making, task orchestration, reasoning, and workflow automation at scale.

Responsibilities:

• Design, develop, and maintain highly scalable backend services using Java and Spring Boot.
• Architect and build microservices-based applications deployed on cloud-native infrastructure.
• Develop and integrate Agentic AI workflows leveraging Large Language Models (LLMs).
• Build AI agents capable of planning, reasoning, tool usage, and autonomous task execution.
• Implement Retrieval-Augmented Generation (RAG) pipelines and knowledge retrieval systems.
• Develop APIs and backend services to support AI-powered products and platforms.
• Optimise application performance, scalability, reliability, and security.
• Collaborate with Data Scientists, AI Engineers, Product Managers, and Architects to deliver innovative solutions.
• Contribute to system design discussions, code reviews, and engineering best practices.
• Monitor and troubleshoot production systems to ensure high availability and performance.
• Drive technical excellence through automation, testing, observability, and continuous improvement.

The core requirements for the job include the following:

Backend Engineering:

• 5-7 years of software development experience.
• Strong proficiency in Java (Java 8/11/17+).
• Hands-on experience with Spring Boot, Spring Cloud, Hibernate/JPA.
• Strong understanding of microservices architecture and distributed systems.
• Experience designing RESTful APIs and event-driven architectures.
• Expertise with relational and NoSQL databases such as PostgreSQL, MySQL, MongoDB, or Redis.
• Strong knowledge of design patterns, data structures, and algorithms.

Agentic AI and GenAI:

• Hands-on experience building Agentic AI applications and AI-powered workflows.
• Experience with LLMs such as GPT, Claude, Gemini, Llama, or similar models.
• Knowledge of RAG architectures, vector databases, and semantic search.
• Experience with frameworks such as LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar.
• Understanding of prompt engineering, agent orchestration, memory management, and tool calling.
• Experience integrating AI models through APIs and deploying AI-enabled applications in production.

Cloud and DevOps:

• Experience with AWS, Azure, or GCP.
• Familiarity with Docker and Kubernetes.
• Experience with CI/CD pipelines and infrastructure automation.
• Understanding of monitoring and observability tools.

Good to Have:

• Experience with MCP (Model Context Protocol).
• Knowledge of AI evaluation frameworks and observability platforms.
• Exposure to multi-agent systems and workflow orchestration.
• Experience with Kafka, RabbitMQ, or other messaging systems.
• Familiarity with graph databases and knowledge graphs.
• Contributions to open-source AI projects.

Nice to Have:

• Strong problem-solving and analytical skills.
• Ability to work in a fast-paced, product-focused environment.
• Passion for emerging AI technologies and intelligent systems.
• Excellent communication and stakeholder collaboration skills.
• Ownership mindset with the ability to drive projects independently.