Senior Software Engineer, Agentic AI

Trustible•Arlington, VA

4h•$145,000 - $165,000

About The Position

We're hiring a Senior Software Engineer to build out Trustible's agentic AI capabilities. This is a backend-heavy engineering role. You'll spend your time writing MCP tool integrations, building agentic data pipelines, and architecting the infrastructure that lets AI agents act reliably inside our platform. You'll also work across our broader Django stack when the work calls for it. The ideal candidate is a strong systems engineer who's genuinely curious about agentic AI and wants to build the infrastructure behind it, not just talk about it. You bring deep backend skill, and we'll give you a fast-moving, high-leverage problem to point it at. Because this is a senior position, you'll operate with real autonomy. You'll make architecture calls, shape scope, and mentor other engineers as the team grows.

Requirements

5+ years of professional backend software engineering experience, with real depth in Python
Strong experience with Django or a comparable web framework, and comfort working across a full stack when needed
Experience building data pipelines: ingestion, transformation, and reliable processing at scale
Familiarity with LLM tool-calling patterns, MCP, or similar agent-orchestration concepts, with genuine excitement about going deeper here
Strong systems thinking. You reason naturally about failure modes, retries, idempotency, and data consistency
A track record of finding good patterns in ambiguous, fast-moving technical spaces
Excellent written communication. You can document a design decision clearly enough that someone else can pick it up and run

Nice To Haves

Experience with async Python (asyncio, FastAPI, or similar) for streaming or long-running agent workloads
Prior experience at an early or growth-stage startup
Exposure to vector databases, embeddings, or RAG architectures
Experience with AWS infrastructure (RDS, Redis, or similar)

Responsibilities

Design and build MCP tool integrations connecting our platform to model providers and external systems
Architect data pipelines that ingest, structure, and process AI agent outputs at scale
Build and maintain core platform features in Django and Python, alongside the agentic work
Make sound tradeoffs between build speed and long-term maintainability, and be able to defend those calls
Partner with our CTO on technical architecture for the agentic roadmap
Set technical standards for agentic development that other engineers can follow as the team grows
Debug and harden systems in production, since agent behavior surfaces failure modes that traditional software doesn't