We are seeking an AI-first Full Stack Java Engineer to design and build next-generation intelligent systems for U.S. government and enterprise platforms.

This role is focused on practical AI engineering — not just integrating APIs, but designing optimized, scalable, and cost-efficient AI systems using LLMs, RAG pipelines, and modern cloud architectures.

You will work on long-term, mission-critical systems involving:

1. Large-scale document ecosystems
2. AI-assisted decision systems
3. Intelligent search and retrieval platforms
4. Secure, compliant, cloud-native applications

This is a fully remote, long-term opportunity with high ownership and direct impact.

🎯 Key Responsibilities

1. Design and build AI-powered full stack applications using Java and modern frontend frameworks
2. Architect and implement RAG (Retrieval-Augmented Generation) pipelines at scale
3. Optimize LLM usage for performance, cost, and accuracy
4. Develop backend services (Java/Spring Boot) for AI orchestration and data pipelines
5. Build intelligent APIs integrating LLMs, vector databases, and enterprise data sources
6. Design and optimize semantic search and document retrieval systems
7. Implement prompt engineering and evaluation strategies for production systems
8. Ensure systems meet security, scalability, and compliance requirements (government-grade)
9. Use AI tools to accelerate development, testing, and system design
10. Collaborate on architecture, product design, and innovation initiatives

🛠 Required Technical Skills

🔷 Core Backend (Java – Mandatory)

1. Strong expertise in Java (Spring Boot / Microservices architecture)
2. REST API design and distributed systems
3. Experience with high-throughput, scalable backend systems

🔷 AI / LLM Engineering (Critical)

1. Hands-on experience with LLMs (OpenAI, Claude, Gemini, or similar)
2. Deep understanding of:
3. RAG architectures
4. Vector databases (Pinecone, Weaviate, FAISS, etc.)
5. Embedding strategies and chunking techniques
6. Experience optimizing:
7. Latency
8. Token usage
9. Cost vs performance trade-offs
10. Prompt engineering and response evaluation techniques
11. Familiarity with frameworks like LangChain, LlamaIndex, or custom pipelines

🔷 Full Stack Development

1. Frontend experience with React / Next.js
2. API integration and UI for AI-driven workflows
3. Understanding of modern component architecture

🔷 Data & Search

1. Experience with Elasticsearch / OpenSearch
2. Handling structured + unstructured data
3. Designing scalable indexing and retrieval systems

🔷 Cloud & DevOps

1. AWS or Azure (cloud-native application development)
2. Docker, CI/CD pipelines
3. Linux environment proficiency
4. Performance optimization and monitoring

🔷 AI-Driven Development (Very Important)

1. Daily use of tools such as:
2. GitHub Copilot / Cursor / Claude / ChatGPT
3. Ability to:
4. Rapidly prototype with AI
5. Automate coding workflows
6. Improve engineering productivity using AI

💡 Preferred Qualifications

1. Experience building AI systems for enterprise or government environments
2. Understanding of secure and compliant architectures (FedRAMP, NIST, etc.)
3. Experience with large document systems or knowledge platforms
4. Exposure to multi-tenant SaaS systems
5. Strong system design and architecture skills

🚀 What You’ll Work On

1. AI-powered knowledge and decision systems
2. Advanced search and retrieval platforms
3. Intelligent document processing and transformation systems
4. Scalable AI orchestration backends
5. Long-term, high-impact government digital platforms

🌟 What We’re Looking For

1. A builder mindset with strong ownership
2. Someone who thinks in systems, not just features
3. Deep curiosity about AI optimization and real-world applications
4. Ability to ship production-grade solutions independently
5. Passion for using AI to solve complex, real-world problems

🎯 Why Join Us

1. Fully remote, long-term stable opportunity
2. Work on mission-critical government systems
3. Build cutting-edge AI platforms (not just integrations)
4. High ownership and autonomy
5. Exposure to real-world AI at scale
6. Competitive compensation

📩 How to Apply

Please share:

1. Resume
2. GitHub / portfolio
3. Examples of AI/LLM/RAG systems you have built
4. A brief note on how you use AI in your daily development workflow

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