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Weekday AI

Weekday AI

Website

Staff Backend Engineer

Company

Weekday AI

Role

Staff Backend Engineer

Job type

Full-time

Found on Mokaru

19 hours ago

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Salary

Not disclosed by employer

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.
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