Role : Principal Engineer
Location : Charlotte NC (Onsite)
Rate : $70
Indent : SF_OP_205828-11 / SF_OP_205828-14
Role Overview
As a Principal Engineer for AI Tools, you will sit at the critical intersection of applied artificial intelligence, developer experience (DevEx), and high-scale distributed systems. You will define the technical strategy and reference architecture for internal AI tools—including autonomous agent hosting, AI-driven code review systems, internal vector/knowledge retrieval bases, and LLM orchestration gateways. This is a senior individual contributor (IC) leadership role focused on multiplying engineering efficiency, establishing security and evaluation best practices, and shaping how hundreds or thousands of engineers build software using AI-native workflows.
Key Responsibilities
Platform Architecture & Tooling Strategy
- Design internal AI platforms: Architect scalable, low-latency internal developer tools, IDE extensions, cloud agent hosting infrastructures, and automated code review pipelines.
- Set technical standards: Define reusable architectural patterns, governance-by-design frameworks, and SDK abstractions for secure LLM consumption across product and engineering teams.
- Drive build vs. buy decisions: Evaluate emerging foundational models, inference engines, vector databases, and developer productivity ecosystems to optimize cost, latency, and quality tradeoffs.
LLM & Intelligent Systems Integration
- Orchestrate AI workflows: Integrate large language models (LLMs), retrieval-augmented generation (RAG), and agentic planning loops into developer and operational tooling.
- Optimize retrieval & context: Build high-performance knowledge retrieval platforms that allow AI tools to safely query internal codebases, documentation, and system telemetry.
- Implement guardrails & evaluation: Deploy rigorous evaluation frameworks to measure tool accuracy, catch behavioral drift, minimize hallucinations, and guard against data leakage or prompt injection.
Technical Leadership & Mentorship
- Multiply team capability: Mentor senior and staff engineers, raise the standard of engineering craftsmanship, and lead through technical influence rather than authority.
- Partner across organizations: Collaborate closely with product management, security, infrastructure, and developer productivity teams to align tool roadmaps with company-wide goals.
- Champion AI-native engineering: Evangelize best practices for AI-assisted development, prompt workflows, and generative AI operations (GenAIOps) across the company.
Required Qualifications & Competencies
Experience & Background
- 10+ years of professional software engineering experience, with at least 5 years operating in a senior, lead, or principal capacity building large-scale backend platforms or developer tooling.
- Demonstrated track record of architecting and shipping complex distributed systems or AI-integrated platforms into production environments.
Technical Hard Skills
- Proficiency in core languages: Expert-level programming skills in Python, Go, Rust, or C++.
- AI & LLM Ecosystem: Deep command of LLM orchestration frameworks (e.g., LangChain, LlamaIndex), vector databases (e.g., Pinecone, Milvus, Qdrant), and RAG architecture design.
- Cloud & Infrastructure: Strong command of containerization and orchestration tooling (Docker, Kubernetes) and modern cloud environments (AWS, GCP, or Azure).
- Systems Design: Exceptional distributed systems design skills, focusing on high availability, low latency, multi-tenancy, and high-throughput data processing.
Core Competencies
- Agentic AI workflows and tool invocation patterns
- Semantic search and hybrid retrieval systems
- Observability, monitoring, and tracing (e.g., OpenTelemetry, MLflow)
- AI security alignment, guardrails, and compliance
Preferred Qualifications
- Experience building internal developer platforms (IDPs) or developer productivity tools at scale.
- Hands-on exposure to fine-tuning smaller open-source models (Llama, Mistral) for specialized domain tasks.
- Contributions to open-source developer ecosystems or AI frameworks