Senior Backend Engineer - Java & Python (2 Positions)

We are seeking a Senior Backend Engineer with expertise in Java, Spring Boot, Python (FastAPI), API design, security, and enterprise platform development. This role focuses on building robust, scalable, and secure backend services that power the Z2 Enterprise Platform, enabling rich functionality across supply chain applications, user workflows, and AI-driven features.

In addition to traditional backend responsibilities, this role includes integrating with Generative AI systems and LLMs, building API endpoints for intelligent assistants, enabling search and indexing via systems like Elasticsearch, and supporting scalable PostgreSQL-based persistence layers. You'll work closely with frontend, DevOps, product, and AI/ML teams to deliver enterprise-grade capabilities with modern architectural patterns.

You will be responsible for designing and implementing secure, high-performance, and extensible backend components that support multi-tenant, microservices-based enterprise applications while also embedding AI-powered workflows and intelligent features using LLMs and vector stores.

The ideal candidate combines deep backend engineering skills with a strong product mindset, and is excited about delivering AI-native enterprise features at scale.

• Design, develop, and maintain backend services and APIs using Java (Spring Boot) and Python (FastAPI).
• Architect systems for scalability, security, and performance in microservices/cloud-native environments.
• Implement modular service layers to support domain logic, integrations, and cross-cutting concerns.

• Optimize PostgreSQL schemas, queries, indexes, and connections for high-performance data access.
• Architect scalable data models and sharding/partitioning strategies for large datasets.
• Proactively monitor and troubleshoot database performance bottlenecks.

• Build secure, versioned RESTful APIs (GraphQL experience is a plus) for web, mobile, and AI integrations.
• Implement structured API contracts with proper governance, validation, and observability.
• Ensure data access follows RBAC/ABAC principles and supports multi-tenant contexts.

• Integrate with LLM platforms (OpenAI, Anthropic, Hugging Face, etc.) to expose AI-powered capabilities via backend services.
• Build RAG (Retrieval-Augmented Generation) flows and streaming pipelines to support GenAI workflows.
• Collaborate with AI/ML engineers to expose model endpoints, prompt templates, and feedback loops via APIs.
• Manage vector databases (e.g., pgvector, Pinecone) and embed AI inference into core platform services.

• Implement strong authentication/authorization using Spring Security, JWT, OAuth2, and SSO.
• Enforce backend security best practices, API rate-limiting, and protection against common vulnerabilities (OWASP).
• Drive code quality through unit testing, static analysis, and CI/CD workflows.

• Collaborate with product managers, frontend engineers, DevOps, and AI/ML teams to define architecture and roadmap.
• Mentor junior developers and conduct code reviews and design walkthroughs.
• Contribute to technical documentation, RFCs, and system design artifacts.

• 5+ years of backend development experience with Java (Spring Boot) and Python (FastAPI or Flask).
• Strong understanding of object-oriented design, microservices, and distributed systems.

• Experience building and managing ETL pipelines for large-scale data ingestion.
• Strong experience with Elasticsearch / OpenSearch, schema design, indexing, and tuning.
• Deep knowledge of PostgreSQL performance optimization, scaling, partitioning, and replication.

• Proficiency in designing REST APIs; familiarity with GraphQL is a plus.
• Experience with Docker, Kubernetes, Helm, and CI/CD pipelines using GitHub Actions, Jenkins, or ArgoCD.

• Hands-on experience with Spring Security, OAuth2, JWT, and secure API practices.
• Familiarity with profiling, monitoring, and performance tuning tools (Prometheus, Grafana, etc.).

• Exposure to LLM integration (e.g., OpenAI, Hugging Face Transformers, LangChain).
• Experience with vector databases, embeddings, and RAG architectures.
• Understanding of AI observability, prompt logging, and feedback-driven refinement is a plus.

• Experience with event-driven architectures (Kafka, RabbitMQ).
• Familiarity with serverless deployments (AWS Lambda, API Gateway).
• Exposure to data observability and anomaly detection tools.
• Prior work on LLMOps or GenAI product workflows is highly desirable.

• Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience).

• Opportunity to work on mission-critical backend systems and data infrastructure.
• Competitive salary and comprehensive benefits package.
• Collaborative and innovative work environment with modern tools and processes.