SDE 1 (AI Team)

Role Overview: You will be joining the aiRA Engineering Team as an SDE I. Your responsibilities will include working alongside senior engineers and product managers to design, build, and scale AI-driven micro-services and internal developer tools that support Capillary's next-generation loyalty stack. This role is suitable for individuals who are enthusiastic about LLM-powered systems, multi-agent orchestration, and various SaaS engineering challenges, ranging from context-layer design to prompt orchestration, workflow automation, and performance optimization. Key Responsibilities: - Design and Develop: Implement high-quality, testable code in Python/NodeJS/Java for aiRA Agents (Config, Analytics, Testing, Support). - Integrate AI workflows: Build APIs and pipelines connecting LLMs, context stores, and brand-specific knowledge graphs. - Work with Data & Context: Support retrieval-augmented generation (RAG), embedding stores, and schema orchestration for brand-aware agents. - Collaborate Cross-Functionally: Collaborate closely with data science, UX, and platform teams to introduce new capabilities (e.g., auto-test suites, predictive models, or self-configuring loyalty flows). - Monitor & Optimize: Instrument performance metrics, write automated tests, and optimize for latency, scalability, and cost-per-task. - Learn Fast, Ship Faster: Contribute to hackathons, PoCs, and internal AI experiments aimed at pushing the boundaries of Generative Loyalty. Qualifications Required: - 02 years of experience in software development (strong internship or academic projects count). - Proficiency in Python, NodeJS, or Java and experience with REST APIs / microservices. - Familiarity with databases (MySQL, PostgreSQL, or MongoDB) and event-driven systems. - Working knowledge of cloud platforms (AWS preferred) and Git workflows. - Bonus: Hands-on experience with LangChain/LlamaIndex, vector stores, or LLM APIs (OpenAI, Bedrock). - Strong problem-solving skills, clean code habits, and attention to detail. - Eagerness to learn AI systems and collaborate in cross-functional teams (product, data, design).,