Companies Weekday AI Staff Software Engineer

About the role

Weekday AI · Onsite

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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