Standard Template Labs

Standard Template Labs

Principal Software Engineer

NYC, NY · Principal

Sponsorship not specified$200k-$250kDetected 315 days ago
PythonJavaGoRustC++Distributed SystemsBackend DevelopmentFull-Stack DevelopmentVector DatabasesDevOpsMachine LearningLLMsRAGLLMOpsLeadershipCollaborationMentoring

About the role

  • This is a deeply hands-on role for a senior technical leader who thrives at the intersection of AI systems, distributed infrastructure, and product-grade software engineering.
  • You'll help us define what "applied, full-stack AI" means at

Responsibilities

  • 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).
  • Continuously evaluate emerging AI frameworks, agent runtimes, orchestration tools, and model APIs, integrating them where they drive real user value.

Requirements

  • 10+ years of professional software engineering experience, including technical leadership in complex, high-scale systems.
  • Proven experience architecting and shipping distributed systems with meaningful AI, automation, or intelligent decisioning components.
  • Hands-on experience with LLMs, embeddings, vector databases, RAG pipelines, agent frameworks, or model integration patterns.
  • Proficiency in at least one modern programming language (Go, Rust, Python, Java, or C++).
  • Experience mentoring senior engineers and driving engineering best practices.
  • Familiarity with AI-assisted development workflows and modern DevOps/tooling.
  • Strong system design skills across APIs, data modeling, event-driven architectures, caching, storage, and performance optimization.
  • Comfort working across the stack, including backend services and collaboration on user-facing or API-layer design.

Nice to have

  • Experience operationalizing ML or LLM workloads in production at scale.
  • Background in microservices, event-driven systems, or real-time data pipelines.
  • Exposure to frontend frameworks or strong product intuition around AI UX.
  • Experience with high-throughput, low-latency, or mission-critical systems.
  • Open-source contributions or demonstrated technical leadership in distributed systems or AI tooling.

Compensation

  • $200,000-$250,000 USD.
  • The reasonably estimated yearly salary for this role at is: $200,000-$250,000 USD.

Benefits

  • Competitive compensation, equity, and a comprehensive benefits package.
  • Design data models and pipelines that support learning, reasoning, and traceability across the platform.

Equal opportunity

  • equal opportunity employer, we don't tolerate discrimination or harassment of any kind.
  • As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind.

Visa & Work Authorization

  • Whether that's based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status or any other protected characteristic as outlined by federal, state or local

This listing is sourced directly from Standard Template Labs's careers page and normalized into a canonical job model.