Lead Software Engineer

Summary

• Engagement: Contractor, hands-on IC-lead (7080% coding; 2030% technical leadership).
• Experience: 812 years total; 35 years leading squads/streams while remaining deep in code.
• Stack: Java, Spring Boot, REST APIs, MySQL/PostgreSQL and MongoDB/Cassandra, Docker/Kubernetes, Git, OAuth2/JWT, one cloud (AWS/GCP/Azure).
• GenAI/AI Tools: Proficient with AI coding copilots and code-generation tooling; experience designing and integrating GenAI services; comfortable with vibe coding workflows.
• Outcome: Ship secure, scalable services quickly; mentor engineers informally; drive design, reliability, CI/CD, and AI-enabled productivity.

Required Qualifications

• 812 years backend/platform engineering with strong, recent hands-on in Java/Spring Boot.
• Designed, built, and scaled RESTful APIs in production; API versioning, schema evolution, and backward compatibility.
• Data depth across MySQL/PostgreSQL and MongoDB/Cassandra; indexing, optimization, and caching patterns.
• Implemented RBAC, OAuth2/OIDC, JWT in real-world systems.
• Proficient with Git workflows (trunk-based or GitFlow), code reviews, and branching strategies.
• Testing: unit, integration, contract (e.g., Pact), and performance tooling; API tooling with Swagger/OpenAPI and Postman.
• Production-grade Docker and Kubernetes experience (deployments, services, ingress, HPA, rollout/rollback).
• Cloud proficiency on at least one of AWS/GCP/Azure (compute, networking, storage, IAM, managed DBs).
• AI Coding Tools and GenAI (new)
• Daily-use proficiency with at least one AI coding tool in IDE/CLI; able to set team guardrails, policies, and best practices.
• Hands-on experience integrating at least one LLM platform (e.g., Azure OpenAI, AWS Bedrock, Vertex AI, or OpenAI/Anthropic APIs) into backend services.
• Practical prompt engineering and evaluation; experience with RAG using vector stores (e.g., OpenSearch, pgvector, Pinecone, Redis) and embeddings.
• Familiarity with model lifecycle concerns: versioning, offline/online evaluation, A/B testing, telemetry, safety/abuse handling.
• Comfort with vibe coding: collaborative AI-assisted workflows, rapid prototyping, live coding with AI agents, and converting exploratory prompts into production-grade code and tests.
• Clear communicator; able to ramp quickly and deliver independently with minimal supervision.