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.