Summary
✨ AI‑Generated
A principal-level engineering role focused on architecting production AI systems and distributed platforms. The position requires deep experience with LLM applications, backend engineering, and technical leadership.
Highlights
Remote leadership role designing advanced AI systems, setting architecture standards, and influencing large-scale engineering decisions.
Description
Title: Principal Software Development Engineer - AI
Location: Remote - able to start 9am EST time
Duration: Permanent - Direct hire
Requirements:
Professional software engineering experience with progressively increasing impact, including multiple years designing and operating production LLM/agentic systems at Staff-level scope or above.Proven technical leadership designing distributed systems and microservices for complex domains, with working knowledge of DDD and Clean Architecture principles applied to build highly performant, well-architected systems (prior DDD project experience not required).Full-stack breadth, spanning modern front-end frameworks and a Python back-end, sufficient to lead architecture across the entire product stack, not just AI services.
.NET/C# experience is a plus, not a requirement.Track record of authoring architecture standards adopted beyond your own team, producing decision records that other senior engineers review, cite, and build on.Demonstrated quantified build-vs-buy decisions against named vendors (e.g., eval/observability platforms, vector stores), with cost models and explicitly rejected alternatives.Deep fluency in the current AI platform landscape: stateful agent orchestration, MCP and inter-agent (A2A) interoperability, eval-gated CI/CD, and vector-enabled persistence (PostgreSQL/pgvector, DiskANN-class indexing, managed offerings).A considered point of view on where the companies model strategy should be in two years, including whether and where to adopt fine-tuned small language models versus frontier APIs, grounded in cost, latency, and control tradeoffs.Experience defining platform boundaries between AI stacks and an existing product stack (e.g., Python AI services alongside .NET), including shared service-kit libraries other teams consume.Security and governance leadership: resource isolation, agentic workflow guardrails, responsible AI in a regulated, money-movement domain.Executive communication, articulating platform tradeoffs in terms leadership can act on, covering cost, risk, and optionality, not just engineering detail.A high degree of agency, building net-new systems and optimizing API performance where no established pattern exists, forging the path rather than waiting for one, with demonstrated ability to bring other engineers along that path.Demonstrated multiplier effect through mentorship: pairing with, unblocking, and growing senior engineers.A passionate and key contributor to the companies software factory, directing and reviewing agentic development while maintaining and improving our high quality and compliance bar.
