Weekday AI
WebsiteStaff Backend Engineer
Company
Role
Staff Backend Engineer
Location
Job type
Full-time
Found on Mokaru
19 hours ago
Salary
Job description
This role is for one of the Weekday's clients
Min Experience: 8 years
Location: Chennai
JobType: full-time
We are seeking a Staff Backend Engineer to design and develop scalable, AI-native backend services that support customer intelligence, campaign orchestration, and attribution on the scale of automotive retail. In this role, you will act as a crucial technical leader—defining hexagonal architecture patterns, overseeing service boundaries, spearheading AI integration strategies, and elevating engineering standards throughout the entire team.
Key Responsibilities
- Design and develop Java microservices (Spring Boot 3.x) following hexagonal architecture principles — creating well-defined domain cores, port interfaces for persistence (MongoDB, PostgreSQL, Cosmos DB), and adapter implementations for Kafka, Elasticsearch, Redis/Aerospike, and external APIs.
- Take full ownership of core domain models and service boundaries from conception through production deployment, including hexagonal design, Kafka event contracts, and ongoing improvements.
- Develop scalable and secure REST APIs alongside resilient Kafka-based event-driven pipelines that handle event consumption and production across various source systems.
- Craft MongoDB document schemas and PostgreSQL relational schemas optimized for high-throughput, multi-tenant environments, with a focus on indexing strategies, TTL configurations, and tenant isolation techniques.
- Design Cosmos DB data models to support high-throughput event and state storage, considering partition key strategies, consistency settings, and TTL management.
- Architect and implement reliable campaign execution workflows using Temporal.
- Define and maintain AI-native integration patterns, including MCP tool registration, scoring model serving contracts, LLM gateway integration, and agentic workflow design.
- Diagnose and address performance bottlenecks across services, Kafka pipelines, data layers, and Elasticsearch query performance.
- Ensure all systems adhere to standards for reliability, scalability, and observability.
- Mentor engineers at various levels—senior, mid-level, and junior—helping to elevate engineering excellence consistently.


