Description

Key Responsibilities

• Lead the design and development of scalable backend and edge-computing solutions.
• Build production-grade APIs and microservices using Java and Spring Boot.
• Develop end-to-end signal flows covering edge detection, ingestion, processing, storage, and downstream routing.
• Implement event-driven architectures, validation pipelines, and data-normalization services.
• Build integrations with identity, trust, security, and third-party technology providers.
• Support JWT validation, token verification, public-key caching, and secure signal ingestion.
• Develop data-access and feature-processing services that support ML inference and model-serving workflows.
• Use AI coding assistants to accelerate development, testing, debugging, documentation, and code reviews.
• Guide engineers on architecture, coding standards, design reviews, and technical problem-solving.
• Collaborate with architects, data scientists, product teams, and external partners.
• Work effectively in a fast-paced, greenfield environment with evolving requirements.

Required Qualifications

• 8+ years of software engineering experience, including technical leadership responsibilities.
• Strong hands-on expertise in Java, Spring Boot, REST APIs, and microservices.
• Experience building distributed systems and event-driven architectures.
• Strong AWS experience across compute, storage, networking, security, and IAM.
• Hands-on experience with edge computing, CDN functions, edge workers, Lambda@Edge, or equivalent technologies.
• Experience with JavaScript or TypeScript-based edge runtimes.
• Experience building greenfield platforms or taking products from zero to one.
• Exposure to ML inference pipelines, model serving, feature pipelines, or AI/data platforms.
• Mandatory hands-on experience with AI-assisted development tools such as GitHub Copilot, Claude Code, Cursor, ChatGPT, or similar tools.
• Ability to demonstrate how AI tools have been used for coding, debugging, testing, documentation, or development-workflow automation.
• Strong communication, mentoring, and problem-solving skills.

Preferred Qualifications

• Python and Databricks experience.
• Experience with AI agents, agentic workflows, prompt engineering, or LLM-based automation.
• Knowledge of JWT, JWS, PKI, OAuth 2.0, and token verification.
• Experience with distributed tracing, structured logging, monitoring, and observability.
• Background in identity, trust, fraud, cybersecurity, or network services

Key Skills

Education

Bachelor's degree