Senior Backend Engineer

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.

Responsibilities:

• Design and build Java (Spring Boot 3 x) microservices following hexagonal architecture with 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

Requirements:

• 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, and multi-tenant isolation.
• PostgreSQL experience: schema design, query optimization, and 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 workflow orchestration.
• Familiarity with AI-native integration patterns: MCP tool registration, scoring API contracts, and 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.