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Weekday, Inc.

Staff Backend Engineer

Posted 9 Days Ago
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In-Office
Chennai, Tamil Nadu, IND
Senior level
In-Office
Chennai, Tamil Nadu, IND
Senior level
Lead design and implementation of scalable Java microservices using hexagonal architecture. Own domain models, Kafka event contracts, and multi-tenant data schemas (MongoDB, PostgreSQL, Cosmos DB). Build resilient REST APIs and Kafka pipelines, optimize performance across services and data layers, integrate AI/LLM model serving and gateways, implement campaign workflows with Temporal, and mentor engineering teams to raise reliability, scalability, and observability standards.
The summary above was generated by AI

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.


Requirements

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.

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