Key Responsibilities

- Design, develop, and maintain full-stack enterprise applications with a strong focus on databases, messaging, APIs, and distributed systems.

- Develop scalable backend services and microservices using Java, Python, Go, .NET, or similar technologies.

- Build responsive frontend applications using React, Angular, or similar modern frameworks.

- Design and implement event-driven architectures using Apache Kafka.

- Develop Kafka producers and consumers, topics, partitions, consumer groups, event processing, and messaging workflows.

- Design and optimize databases using MongoDB and PostgreSQL.

- Develop database schemas, queries, indexes, stored procedures, and data-access layers for high-performance applications.

- Perform database performance tuning, troubleshooting, capacity planning, and optimization.

- Build and integrate RESTful APIs and microservices for enterprise applications.

- Work with Apigee for API management, security, routing, policies, traffic management, and API lifecycle management.

- Implement application monitoring and observability using Splunk and Grafana.

- Develop dashboards, alerts, logs, metrics, and monitoring solutions to identify application, database, and messaging issues.

- Troubleshoot production issues involving applications, databases, Kafka, APIs, infrastructure, and distributed services.

- Design highly available, scalable, resilient, and fault-tolerant systems capable of handling high transaction and message volumes.

- Integrate Generative AI capabilities into enterprise applications, workflows, APIs, or developer solutions.

- Leverage GenAI/LLM technologies to improve application functionality,



automation, analytics, and engineering productivity.

- Implement secure coding, authentication, authorization, data protection, and API security practices.

- Collaborate with DevOps, Cloud, Architecture, Security, QA, Data Engineering, and Product teams.

- Participate in application modernization and migration initiatives, including legacy modernization and event-driven architecture adoption.

- Perform code reviews, technical design reviews, debugging, performance tuning, and production support.

- Create technical documentation for application architecture, APIs, database designs, Kafka workflows, and operational processes.

Required Technical Skills

- 8–12 years of software engineering experience with strong hands-on development experience.

- Strong full-stack development experience with backend and frontend technologies.

- Hands-on experience with Apache Kafka, including producers, consumers, topics, partitions, consumer groups, offsets, and event-driven architecture.

- Strong experience with MongoDB, including schema design, indexing, aggregation, queries, and performance optimization.

- Strong experience with PostgreSQL, including database design, SQL queries, indexing, optimization, and troubleshooting.





- Hands-on experience with Splunk for centralized logging, log analysis, monitoring, and troubleshooting.

- Hands-on experience with Grafana for dashboards, metrics, visualization, monitoring, and alerting.

- Experience with Apigee or equivalent API management platforms.

- Robust understanding of REST APIs, Microservices, distributed systems, and event-driven architecture.

- Experience with Generative AI, LLMs, AI-enabled applications, or AI-assisted software development.

- Strong programming skills in Java, Python, Go, .NET, or similar languages.

- Hands-on frontend experience with React, Angular, or equivalent technologies.

- Strong understanding of Git, CI/CD, testing, deployment automation, and software engineering best practices.

Preferred Skills

- Experience with cloud platforms such as AWS, Azure, or GCP.

- Experience with Kubernetes, Docker, and cloud-native applications.

- Experience with Kafka Streams, Schema Registry, Kafka Connect, or similar Kafka ecosystem technologies.

- Experience with MongoDB Atlas or managed database platforms.

- Experience with PostgreSQL high availability, replication, and disaster recovery.

- Knowledge of observability practices involving logs, metrics, traces, and distributed monitoring.

- Experience integrating LLM APIs, AI agents, RAG, or GenAI capabilities into enterprise applications.

- Knowledge of API security, OAuth2, JWT, authentication, and authorization.

- Strong problem-solving, analytical, communication, and collaboration skills.

Pay: ₹2,500,000.00 - ₹3,000,000.00 per year

Work Location: In person

📌 Database and Messaging Software Engineer ( Chennai, Bangalore and Hyderabad) (Bengaluru)
🏢 Navat Technologies
📍 Bengaluru