Backend Lead - Microservices Architect

About Us

Role Overview

Key Responsibilities

• Design and implement microservices-based architectures for large-scale enterprise applications.
• Define API standards, communication protocols (REST, gRPC), and service contracts.
• Lead migration from monolithic systems to microservices, ensuring minimal downtime and data integrity.
• Architect containerized solutions using Docker and Kubernetes, including Helm for deployment
• Design multi-agent workflows that interact seamlessly with existing enterprise APIs using LangGraph or similar agent orchestration frameworks (e.g., CrewAI, Microsoft AutoGen, or Semantic Kernel).
• Implement observability practices including logging, metrics, and distributed tracing (Prometheus, Grafana, OpenTelemetry).
• Architect scalable solutions for the efficient handling of memory and context window limits, enabling AI agents to reliably maintain short-term state and long-term memory across stateless distributed environments.
• Ensure security best practices across services (OAuth2, JWT, API Gateway, rate limiting).
• Collaborate with product owners, developers, and DevOps teams to align architecture with business goals.
• Mentor engineering teams on microservices principles, domain-driven design, and event-driven architecture.

Required Skills & Qualifications

• 12+ years of experience in software development with at least 5 years in microservices architecture.
• Strong knowledge of distributed systems, service discovery, and API management.
• Exposure to MLOps and AI system observability.
• Hands-on experience with Docker, Kubernetes, and Helm for container orchestration.
• Design multi-agent workflows that interact seamlessly with existing enterprise APIs using LangGraph or similar agent orchestration frameworks such as CrewAI, Microsoft AutoGen, or Semantic Kernel.
• Proficiency in designing RESTful and gRPC APIs, and implementing API gateways
• Enhance information architecture using Knowledge Graphs (e.g., Neo4j, Amazon Neptune, or GraphDB) to improve semantic data retrieval, enrich RAG pipelines, and ground data for use in complex agentic workflows.
• Hands-on experience with LLM-based applications and agentic frameworks.
• Expertise in cloud platforms (AWS, Azure, GCP) and cloud-native patterns.
• Knowledge of event-driven architecture, messaging systems (Kafka, RabbitMQ), and data consistency strategies.
• Strong understanding of security, scalability, and fault-tolerance in distributed systems.

Preferred Qualifications

• Experience with service mesh technologies (Istio, Linkerd).
• Familiarity with domain-driven design (DDD) and CQRS patterns.
• Knowledge of advanced observability and chaos engineering practices.
• Experience with CI/CD tools (Jenkins, GitHub Actions, Azure DevOps) and Infrastructure as Code (Terraform, Ansible).