Principal AI Engineer
$178,900–$198,000 year
HybridReston, Virginia, United States
Job Summary
Own and enable Stanley Martin's agentic AI platform by configuring enterprise tooling, MCP servers, and secure connectors to core business systems like ERP and HR. Build production agentic systems end-to-end, implementing patterns such as tool calling, planner-executor flows, and human-in-the-loop controls while establishing version-controlled repositories of reusable skills and reference architectures. Define evaluation harnesses, observability standards, and governance guardrails to ensure safe, accurate agent deployment across diverse environments including Microsoft Dynamics and Salesforce. Partner with business stakeholders to map workflows, operationalize semantic models, and drive adoption through internal showcases and technical leadership.
Required Qualifications
- 8+ years of professional engineering experience, with a track record of designing, shipping, and operating production systems
- Bachelor's degree in computer science or a related field, or equivalent practical experience
- Hands-on experience building with LLM APIs, agent frameworks, or AI-powered applications that ran in production or were used by real people, including agentic patterns such as tool use, orchestration, and human-in-the-loop design
- Depth with modern agentic AI toolchains and coding agents including Anthropic Claude, Snowflake, Omni, and MCP-based architectures, or a demonstrated ability to develop that depth quickly, including connector and tool integration, skill and subagent design, and prompt engineering
- Cloud fluency, with Microsoft Azure strongly preferred; experience with enterprise cloud data platforms (e.g., Snowflake or comparable)
- Evaluation and testing discipline: you can define what good means for an agent and prove it before production
- Security- and governance-minded: comfortable with data classification, least-privilege design, auditability, and human-in-the-loop controls
- Strong proficiency in Python
- Willingness to work in a hybrid environment (3 days per week onsite at Reston, VA headquarters)
Desired Qualifications
- Comfort with additional languages (TypeScript/JavaScript, SQL) is a plus
- Experience building shared AI infrastructure or developer platforms that enable multiple teams to build on your foundation
- Familiarity with multi-agent orchestration patterns: task decomposition, tool-use pipelines, agent memory, and human-in-the-loop workflows
- Experience with retrieval-augmented generation, embeddings, vector search, and unstructured-document pipelines (ingestion, chunking, metadata enrichment)
- Experience with LLMOps/MLOps tooling: model registries, CI/CD, monitoring and observability, drift detection, and cost controls
- Experience with the Microsoft AI ecosystem (Copilot Studio, Azure AI Foundry, Power Platform) and judgment about when to lean in versus build
- Experience turning ambiguous business processes into working agents in a non-tech industry (construction, real estate, manufacturing, financial services)
- Track record of mentoring engineers and influencing senior technical and business leaders
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