About the Job
As a Full Stack Software Developer (IP Tools & AI Development), you’ll help build scalable IP platforms enhanced with AI/LLM capabilities. This role is for systems thinkers who can go beyond prompt creation—designing end-to-end solutions that combine robust web applications, patent analytics, and intelligent automation workflows. You’ll ship features that rely on RAG pipelines, agentic tool use, and evaluation frameworks, while optimizing for cost, latency, and quality across the stack.
Roles & Responsibilities
- Design and develop full-stack applications for IP tools, analytics, and platforms.
- Build scalable backend services, APIs, and databases; implement responsive frontends with modern JS frameworks.
- Implement AI-powered capabilities such as RAG pipelines (ingestion, embeddings, vector search, re-ranking).
- Create agentic workflows including planning, multi-step reasoning, tool calling, and memory mechanisms.
- Develop prompt engineering and evaluation pipelines to measure and improve LLM outputs over time.
- Integrate with LLM APIs (e.g., OpenAI, Claude) while optimizing for cost, latency, and quality.
- Work with third-party APIs, event-driven systems, and database integrations for automation use cases.
- Partner with IP analysts, product teams, and designers to translate business needs into secure, high-performing solutions.
- Support SDLC activities including testing, deployment, and performance and security improvements.
Required Skills & Qualifications
- Bachelor’s degree in Computer Science, IT, or related field.
- 4–6 years of proven full-stack development experience.
- Strong proficiency in frontend: React / Angular / Vue, plus HTML, CSS, and JavaScript.
- Strong backend skills with Node.js or Python or Java or .NET.
- Database experience with MySQL, PostgreSQL, and/or MongoDB.
- Experience building REST APIs and microservices on cloud platforms like AWS / Azure / GCP.
- Deep understanding of RAG components: embeddings and vector search concepts.
- Hands-on work with LLM APIs (OpenAI, Claude), prompt engineering, and chaining.
- Familiarity with vector databases such as Pinecone, Weaviate, or Milvus.
- Experience with AI-assisted development tools (e.g., GitHub Copilot) and modern engineering practices.
- Solid knowledge of Git and Agile methodologies, with comfort across the SDLC.
- Preferred: IP domain exposure (patent search/analytics), agent frameworks (LangChain/LlamaIndex), and event-driven or streaming systems.