Principal Software Engineer

Standard Template Labs is a stealth-mode, AI-native startup reimagining the future of IT Service and Configuration Management. They are seeking a Principal Software Engineer to own the technical vision for AI design and implementation across their platform, focusing on building production AI systems and mentoring engineers.

Responsibilities:

• Architect the core intelligence layer of the platform, spanning data ingestion, embeddings, retrieval, graph reasoning, agents, and real-time inference
• Define how LLMs and predictive models integrate across backend services, APIs, and user-facing experiences
• Identify high-impact opportunities where generative, predictive, or autonomous AI can eliminate operational toil, improve system understanding, or enhance decision-making
• Lead architectural decisions around model selection, evaluation, fine-tuning, and inference infrastructure (custom vs OSS vs managed APIs)
• Establish best practices for AI-first engineering, including prompt and schema design, context assembly, evaluators, guardrails, observability, and continuous model monitoring
• Partner with product and leadership to align AI capabilities with customer outcomes, trust requirements, and long-term platform strategy
• Build end-to-end AI-powered features - from backend reasoning services to APIs and user-facing workflows
• Design and implement production-grade LLM and agent workflows, including automated enrichment, anomaly explanation, topology discovery, change impact analysis, and natural language querying
• Develop scalable backend systems for high-throughput inference, embedding generation, vector search, and graph traversal
• Collaborate on or directly contribute to frontend experiences that make AI outputs understandable, actionable, and debuggable for users (e.g., explanations, confidence signals, provenance, and feedback loops)
• Implement retrieval-augmented generation (RAG) pipelines and hybrid search systems that combine structured data, graphs, and unstructured context
• Write clean, well-structured, production-quality code—and champion AI-assisted development tools (Claude, Cursor, Windsurf, etc.) to improve velocity and correctness
• Continuously evaluate emerging AI frameworks, agent runtimes, orchestration tools, and model APIs, integrating them where they drive real user value
• Design data models and pipelines that support learning, reasoning, and traceability across the platform
• Build and evolve distributed systems that are observable, fault-tolerant, and cost-efficient under AI workloads
• Partner with infrastructure and DevOps teams to shape deployment, scaling, monitoring, and rollback strategies for AI-driven services
• Ensure AI systems meet enterprise requirements for reliability, security, explainability, and compliance
• Mentor engineers on full-stack AI patterns, system design for AI workloads, and practical approaches to shipping intelligent features
• Lead architecture reviews and technical deep-dives focused on reliability, safety, performance, and user trust
• Influence engineering standards and culture, emphasizing craftsmanship, clarity, and ownership across the stack
• Help attract and develop top-tier engineering talent excited about AI-native, product-driven systems