Summary :

Engagement : Contractor, hands-on IC-lead (70-80% coding; 20-30% technical leadership).

Experience : 8-12 years total; 3-5 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 :

- 8 to 12 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.