Senior Software Engineer, AI Platform

About the role

Remote based role open to candidates in the USA across Mountain, Central, and Eastern time zones. The AI Platform team builds the foundation for BigPanda's generative AI products for IT Operations, including unified data connectors, secure ingestion and indexing, unified identity and access, and shared agentic infrastructure behind AI-powered incident response, prevention, automation, knowledge retrieval, and operational intelligence. The team moves quickly, works directly with customers, makes pragmatic tradeoffs, and prioritizes shipping differentiated customer value. Engineers are expected to operate with extreme ownership, high urgency, and a strong bias for action.

Responsibilities

• Build production-grade software across backend services, APIs, data ingestion pipelines, enterprise integrations, web applications, workflow systems, and automation platforms.
• Build and own secure, reliable ingestion of customer data from enterprise systems like ServiceNow and Snowflake, so our AI products have the context they need.
• Architect and implement AI-native capabilities using LLMs, prompting, tool calling, agent orchestration, RAG, vector search, knowledge graphs, embeddings, and structured/unstructured enterprise data.
• Use AI coding platforms such as Cursor, Claude Code, and similar tools as a core part of your development workflow to increase speed, exploration, and delivery quality.
• Write high-quality prompts for development, debugging, product behavior, agent execution, data extraction, reasoning workflows, and customer-facing AI experiences.
• Propose, design and own features from concept through delivery, including customer discovery, technical design, implementation, manual validation, release, bug resolution, and iteration.
• Work directly and build relationships with customers, GTM, product, and other engineers to identify high-value problems and translate them into product capabilities.
• Make pragmatic tradeoffs between speed, quality, reliability, cost, latency, scalability, and customer impact.
• Move fast in ambiguous problem spaces