Lead / Principal Java Engineer

Role Overview

We are seeking a highly experienced Lead / Principal Java Engineer to design and build next-generation distributed systems across backend services, edge computing, and AI/ML platforms.

This is a hands-on technical leadership role for an engineer who can take complex systems from 0 to 1, make architectural decisions, and write production-quality code. The ideal candidate thrives in an ambiguous, fast-moving environment and enjoys working across multiple technical domains.

Key Responsibilities

• Design and build end-to-end distributed systems spanning edge detection, ingestion APIs, processing, storage, and downstream services.
• Develop highly scalable backend services using Java and Spring Boot.
• Design and implement APIs, microservices, event-driven architectures, and data processing pipelines.
• Architect and develop solutions using AWS and edge/CDN computing technologies.
• Build solutions for data normalization, feature pipelines, and ML model serving/integration.
• Design third-party integrations including identity, authentication, token validation, and secure data exchange.
• Make technical decisions around storage, reliability, observability, security, and governance.
• Work closely with data science, product, and engineering teams to move AI/ML capabilities from experimentation into production.
• Lead technical design discussions and communicate architecture decisions across teams.
• Take ownership of greenfield initiatives from concept through implementation and production.
• Use AI-assisted development tools such as GitHub Copilot and LLM-based coding assistants to improve engineering productivity.
• Mentor other engineers and provide technical leadership through hands-on development and design.
• 10+ years of experience building production distributed systems.
• Strong expertise in Java and Spring Boot.
• Extensive experience with REST APIs, microservices, event-driven architectures, and distributed systems.
• Strong AWS experience across compute, storage, networking, and IAM.
• Hands-on experience with edge computing, CDN execution environments, edge workers, Lambda@Edge, or similar technologies.
• Experience building data platforms or systems supporting ML inference and model serving.
• Strong understanding of system design, scalability, reliability, observability, and security.
• Proven experience taking systems from 0 to 1 in an environment with evolving requirements.
• Strong communication skills with the ability to influence technical decisions across teams.
• Demonstrated experience using AI-assisted development tools and LLM-powered engineering workflows.

Nice to Have

• JavaScript / TypeScript experience.
• Python experience for data engineering or scripting.
• Databricks or similar data/AI platforms.
• Experience with ML model registries and feature platforms.
• Knowledge of JWT/JWS, PKI, OAuth 2.0, identity, or token verification.
• Experience with distributed tracing, structured logging, and observability platforms.
• Experience building multi-party integrations or network/platform services.
• Open-source contributions.