Full Stack Engineer

Senior Full Stack Engineer – Java, Spring Boot & AIAbout Code17Code17 provides technology consulting and professional services across data engineering, cloud, full-stack development, and agentic AI. We help enterprises build modern applications and implement AI solutions that improve business operations.
Role OverviewWe are seeking a Senior Full Stack Engineer with strong Java and Spring Boot expertise and hands‑on experience building AI-powered applications. The ideal candidate can develop applications across the frontend and backend while integrating large language models, Retrieval-Augmented Generation (RAG), and Model Context Protocol (MCP).
This role requires practical software engineering experience, including taking AI capabilities from prototypes into secure, reliable production applications.
Key Responsibilities
Design, develop, and maintain applications using Java, Spring Boot, and React or Angular.
Build REST APIs, microservices, and integrations with enterprise systems.
Develop RAG pipelines covering document ingestion, parsing, chunking, embeddings, vector retrieval, reranking, and grounded response generation.
Integrate LLMs through cloud AI platforms or model provider APIs.
Build and integrate MCP servers and clients to connect AI applications with enterprise tools, APIs, and data sources.
Implement AI workflows using tool calling, structured outputs, and orchestration frameworks.
Apply authentication, authorization, and data access controls across application and AI workflows.
Evaluate AI response quality, retrieval accuracy, latency, and cost;
troubleshoot failures and improve performance.
Write automated tests, participate in code reviews, and support CI/CD and production releases.
Collaborate with product owners, architects, and business stakeholders to translate requirements into working solutions.
Required Qualifications
5+ years of professional software development experience, with strong hands‑on Java and Spring Boot expertise.
Strong understanding of REST API design, microservices, object‑oriented programming, and design patterns.
Experience with relational databases such as PostgreSQL or MySQL, including SQL development and performance tuning.
Hands‑on experience developing LLM-powered applications beyond basic chatbot integrations.
Practical experience implementing RAG, including embeddings, vector databases, retrieval strategies, and metadata filtering.
Experience implementing or integrating MCP servers or clients, with an understanding of tool discovery, invocation, and access controls.
Experience with prompt design, tool/function calling, structured outputs, and managing model context.
Familiarity with vector search platforms such as Qdrant, pgvector, Pinecone, OpenSearch, or equivalent.
Experience with Git, automated testing, Docker, and CI/CD pipelines.
Strong problem‑solving, communication, and collaboration skills.
Preferred Qualifications
Experience with Spring AI, LangChain4j, or comparable Java AI frameworks.
Python experience for AI services, data processing, or orchestration.
Experience with Amazon Bedrock, Azure OpenAI, Google Vertex AI, or comparable AI platforms.
Familiarity with agent frameworks such as LangGraph, Semantic Kernel, or AWS Strands.
Experience with hybrid search, reranking, and retrieval evaluation.
Understanding of prompt injection risks, sensitive data protection, and safe execution of AI‑invoked tools.
Experience with Kubernetes, messaging platforms such as Kafka, and cloud deployment.
Experience implementing human approval steps, retries, audit logs, and observability for AI workflows.
What Success Looks Like
Deliver maintainable full-stack features with reliable backend services and intuitive user interfaces.
Build AI capabilities that retrieve relevant information and produce grounded, useful responses.
Connect AI workflows securely to enterprise systems through well‑designed APIs and MCP integrations.
Demonstrate measurable improvements in application reliability, AI quality, response time, and operating cost.
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