Lead Software Engineer

3 weeks ago

Bhavnagar, India Grid Dynamics Full time

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 8–12 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.

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