About this role
This role is for one of Weekday’s clients Salary range: Rs 3000000 - Rs 9000000 (ie INR 30 - 90 LPA)
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Experience
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5+ years
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Location: Bengaluru
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JobType: full-time
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We are looking for an experienced Senior Backend Software Engineer to design, develop, and operate highly scalable, secure, and reliable backend systems. The role involves architecting low-latency, real-time microservices that process and detect sensitive data at scale while ensuring high availability, performance, and security.
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The ideal candidate will have strong expertise in distributed systems, backend engineering, data processing, and cloud infrastructure. You will contribute to the architecture of mission-critical services, real-time data ingestion pipelines, machine learning inference systems, and advanced search and agentic AI solutions. This role requires a hands-on engineer with proven technical leadership and the ability to solve complex business and engineering challenges.
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Requirements
Key Responsibilities
1. Backend Architecture and Development
- Design, build, and maintain highly available, secure authentication systems and API services.
- Develop and operate low-latency microservices capable of handling high-throughput workloads.
- Maintain and evolve mission-critical internal databases, backend services, and distributed architectures.
- Ensure production systems meet stringent standards for reliability, scalability, performance, and security.
2. Distributed Systems and Infrastructure
- Architect, optimise, and operate high-volume, auto-scaling infrastructure for real-time data ingestion and processing.
- Build and maintain systems that process substantial data volumes, including several terabytes per day, or support millions of users.
- Develop and improve machine learning inference infrastructure and other latency-sensitive backend services.
- Implement monitoring, observability, and reliability practices for production-grade distributed systems.
- Contribute to cloud infrastructure and deployment automation using modern DevOps tools and practices.
3. Search and Agentic AI Systems
- Design and develop scalable search systems and agentic workflows capable of supporting high levels of concurrency.
- Improve large language model (LLM) accuracy, cost efficiency, and scalability through effective prompt and context engineering.
- Work on capabilities such as data ingestion, text summarisation, semantic search, traditional search, and agent orchestration.
- Optimise system performance and resource utilisation for AI-powered applications.
4. Data Processing and Database Management
- Build and maintain large-scale and real-time data processing pipelines.
- Work with relational and NoSQL databases to support high-volume, distributed workloads.
- Design and optimise data processing architectures using technologies such as PostgreSQL, Kafka, Flink, Snowflake, Hadoop, and ZooKeeper.
- Ensure data systems deliver reliable ingestion, processing, storage, and retrieval at scale.
5. Observability and Documentation
- Build scalable observability systems that provide detailed insights into customer usage, system performance, and service reliability.
- Establish effective monitoring and troubleshooting practices across distributed services.
- Create and maintain technical documentation for internal systems, public APIs, and backend services.
6. Technical Leadership and Collaboration
- Lead the decomposition and resolution of complex technical and business problems.
- Drive architectural decisions and contribute to engineering best practices.
- Mentor engineers and collaborate with cross-functional teams to deliver reliable, production-ready solutions.
- Take ownership of system design, implementation, deployment, and ongoing optimisation.
Required Skills and Qualifications
- 6+ years of professional software engineering experience, with demonstrated technical leadership and expertise in scalable, distributed architectures.
- Strong proficiency in one or more programming languages, such as Python, Go, Java, or C++, with the willingness to learn additional technologies.
- Strong foundation in computer science fundamentals, data structures, and algorithms.
- Proven experience building and operating scalable systems handling thousands of requests per second (RPS), with high reliability targets such as 99.99% availability.
- Experience designing complex distributed systems that process substantial data volumes or support millions of users.
- Hands-on experience developing low-latency, high-throughput microservices and deploying production-grade systems.
- Strong knowledge of distributed storage and database technologies, including SQL and NoSQL databases such as PostgreSQL and Cassandra.
- Experience building and maintaining large-scale or real-time data processing pipelines.
- Strong understanding of production monitoring, observability, performance optimisation, and system reliability.
- Ability to break down complex business requirements into scalable technical solutions and lead implementation effectively.
Must-Have Skills
- Python
- Go
- Java
Good-to-Have Skills
- Node.js
- React
- Redis
Technology Stack
The engineering environment includes:
- Programming Languages: Go, Python, Node.js
- Frontend Technologies: React
- Databases and Storage: Cassandra, Redis, SQL databases
- Cloud and Infrastructure: AWS, Terraform
- Containerisation and Orchestration: Docker, Kubernetes
- Streaming and Networking: Kafka, Envoy
Preferred Experience
- Experience building large-scale search or agentic AI systems.
- Familiarity with semantic search, text summarisation, prompt engineering, context engineering, and agent orchestration.
- Experience with machine learning inference systems and real-time data ingestion infrastructure.
- Knowledge of distributed data processing technologies such as Flink, Snowflake, Hadoop, and ZooKeeper.