About the Role
We are seeking a Full Stack Software Developer who thinks in systems (not just prompts) and can build scalable IP tools enhanced with AI/LLM capabilities. The role involves end-to-end development of IP platforms, including patent analytics and intelligent automation workflows.
Key Responsibilities
- Design and develop full-stack applications for IP tools and platforms.
- Build scalable backend services, APIs, and databases; develop responsive frontends.
- Implement AI-powered features, including:
- RAG pipelines (document ingestion, embeddings, vector search, re-ranking)
- Agentic workflows (tool calling, planning, memory, multi-step reasoning)
- Prompt engineering and evaluation pipelines
- Work with LLM APIs (e.g., OpenAI, Claude) optimizing cost, latency, and quality.
- Develop integrations with databases, third-party APIs, and event-driven systems.
- Collaborate with IP analysts, product teams, and designers to translate business needs into technical solutions.
- Optimize performance, scalability, and security; participate in SDLC, testing, and deployment.
- Leverage AI coding tools (e.g., Claude, GitHub Copilot) for rapid prototyping and development.
Required Skills & Qualifications
- Bachelor’s degree in Computer Science, IT, or related field.
- Proven full-stack development experience.
- Strong proficiency in:
- Frontend: HTML, CSS, JavaScript, React / Angular / Vue
- Backend: Node.js / Python / Java / .NET
- Databases: MySQL, PostgreSQL, MongoDB
- Experience with REST APIs, microservices, and cloud platforms (AWS/Azure/GCP).
- Strong understanding of:
- RAG architectures, embeddings, and vector search
- LLM APIs (OpenAI, Claude), prompt engineering, and chaining
- Familiarity with vector databases (Pinecone, Weaviate, Milvus).
- Experience using AI-assisted development tools (e.g., GitHub Copilot).
- Knowledge of SDLC, Git, and agile methodologies.
Preferred Skills (Good to Have)
- Experience in IP domain tools (patent search, analytics, IP management systems).
- Exposure to agent frameworks (LangChain, LlamaIndex) and real-world AI feature deployment.
- Experience with web scraping, large datasets, streaming/WebSockets, or event-driven systems.
- Hands-on with patent databases (USPTO, EPO, WIPO).
- Exposure to Kubernetes or advanced cloud deployments.
