Senior Software Engineer

Role Overview

We are looking for a Senior Backend Engineer to design, build, and scale robust backend services that power complex business workflows. This role requires strong ownership, deep Java expertise, a solid grounding in hexagonal architecture, and the ability to collaborate effectively across product, QA, AI/ML, and engineering teams in a fast-moving, AI-native environment.

Key Responsibilities

• Design and build Java (Spring Boot 3.x) microservices following hexagonal architecture — clean domain logic isolated from MongoDB, PostgreSQL, Cosmos DB, and Kafka adapter implementations.

• Develop and maintain REST APIs, Kafka event consumers/producers, and domain service logic for campaign, scoring, attribution, and customer profile workflows.

• Build and manage MongoDB document schemas and PostgreSQL relational schemas for high-throughput, multi-tenant use cases. 

• Implement Cosmos DB data models for event and state storage with appropriate partition key and consistency strategies.

• Take end-to-end ownership of components — from domain design and hexagonal adapter implementation through deployment and ongoing optimization.

• Integrate with Elasticsearch for campaign search, customer lookup, and full-text query workloads.

• Configure and tune Redis or Aerospike for frequency cap enforcement, scoring cache, and session state management.

• Identify and resolve performance bottlenecks across services, event pipelines, and data layers.

• Participate actively in design discussions, architecture decisions, and code reviews.

• Mentor Junior engineers and act as a role model for code quality, hexagonal design, and AI-native engineering best practices.

Skills & Qualifications

• 5+ years of backend engineering experience; Bachelor's or Master's degree in Computer Science or a related field.

• Strong Java 21 and Spring Boot 3.x expertise; solid grasp of hexagonal architecture and clean domain modeling.

• Experience with Kafka: consumer/producer patterns, at-least-once delivery, idempotent processing, and event-driven service design.

• Hands-on MongoDB experience: document schema design, indexing, aggregation pipelines, multi-tenant isolation.

• PostgreSQL experience: schema design, query optimization, migration management.

• Familiarity with Cosmos DB or equivalent distributed key-value / document stores.

• Experience with Elasticsearch for search and analytics workloads.

• Experience with Redis or Aerospike for high-throughput caching patterns.

• Familiarity with cloud-based systems on AWS (EKS, MSK, S3).

• Strong debugging, performance tuning, and system optimization skills.

• Familiarity with Agile/Scrum development practices and CI/CD pipelines.

Good to Have

• Experience with Temporal for workflow orchestration.

• Familiarity with AI-native integration patterns: MCP tool registration, scoring API contracts, LLM gateway usage.

• Working knowledge of Python for understanding AI/ML service outputs and integrating scoring results.

• Background in enterprise-scale SaaS platforms: eCommerce, supply chain, or similar.