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# Principal Engineer - Agentic AI Applications

- **Company:** SERKO, LLC
- **Location:** Washington, DC, United States
- **Experience:** Experienced
- **Salary:** $168,000.0 - $240,000.0
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Software Quality, Memory Management, Python (Programming Language), Node.Js, Software Engineering, TypeScript, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Backend, Agentic-AI, CrewAI, AutoGen, AIOps
- **Published:** October 13, 2026
- **Apply:** https://www.careerjet.com/jobad/us92864d98e77179bdca20e3dc8b474aa0

## About the Role

* The Experience: 12+ years of software engineering experience, with at least 4+ years in technical leadership or principal-level roles.
 * The Expertise: Deep hands-on experience shipping LLM-powered or agentic systems to production (utilizing frameworks like LangGraph, AutoGen, CrewAI, or custom-built runtimes).
 * The Systems Mindset: A proven track record of architecting distributed, high-availability systems. You understand that "it worked on my machine" is not the same as "it works at scale."
 * The Toolkit: Mastery of Python and modern backend frameworks. Deep familiarity with RAG pipelines, vector databases, tool-calling APIs, and multi-step reasoning. (TypeScript/Node.js is a plus).
 * The Communicator: Ability to distill complex "black box" AI concepts into clear technical roadmaps for executive stakeholders and cross-functional partners.
 * The Culture: A desire to influence org-wide engineering culture, prioritizing code quality, observability, and rigorous testing in an AI-first world.

## Description

We aren't just building prototypes; we are building the autonomous backbone of the modern enterprise. As a Principal Engineer, you will lead the technical vision and architecture for our next-generation agentic AI applications.
What You'll Do

 * Architect the Agentic Runtime: Own the end-to-end technical architecture for agentic systems, including multi-agent orchestration, memory management, and reasoning pipelines.
 * Engineering for Reliability: Implement robust infrastructure to handle non-deterministic loops, including automated circuit-breakers, latency-aware orchestration (targeting P99 SLAs), and granular token/cost-observability.
 * Set the Standard: Define engineering patterns, design standards, and best practices for agentic application development across the entire organization.
 * Scale the Team: Mentor and grow Senior engineers; conduct deep-dive architecture reviews and drive high-stakes technical decision-making and be instrumental in the hiring process.
 * Bridge the Gap: Partner with AI Ops to ensure agentic workloads are efficiently built, served, and monitored with state-of-the-art observability.