> Markdown version of [/jobs/ext/4357726-architect-production-ready-agentic](https://www.wearedevelopers.com/jobs/ext/4357726-architect-production-ready-agentic). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Architect Production-Ready Agentic

- **Company:** DigitalOcean, LLC
- **Location:** San Francisco, CA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $167,000.0 - $209,000.0
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Artificial Intelligence, Systems Engineering, Distributed Computing Environment, Python (Programming Language), Machine Learning, Digitalocean, Tensorflow, Pytorch, Delivery Pipeline, Large Language Models, Multi-Agent Systems, Deep Learning, Agentic-AI, Fastapi, Information Technology, AutoGen
- **Published:** October 16, 2026
- **Apply:** https://startup.jobs/forward-deployed-applied-scientist-ii-agentic-ai-digitalocean-10483519

## About the Role

* 6+ years of hands-on experience in Applied AI, Machine Learning, or Data Science.
 * Expertise in Multi-agent Frameworks: Proven experience building multi-agent orchestration engines, tool-use / function-calling pipelines, MCP, structured outputs, dynamic planning, and persistent memory models.
 * Production Python & Systems Engineering: Strong skills in writing clean, production-ready Python (Pydantic, FastAPI, Asyncio, PyTorch).
 * Customer-Facing Engineering Mindset: High empathy, crisp technical communication, and the ability to articulate complex AI trade-offs to both engineering leads and executive sponsors.
 * The DO "Shark" Mentality: You think big, bold, and scrappy. You have a bias for action and a powerful sense of ownership over the customer experience., * Education: Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related technical field.
 * Applied Science Experience: Experience in deep learning frameworks (like PyTorch or TensorFlow), distributed training tools as well as various agentic AI frameworks. Solid understanding of various types of transformers and state space models.
 * Research Experience: Experience in publications, patents and Knowledge of latest research in the field of LLM, VLM, Agentic frameworks.
 * Customer Empathy & Technical Leadership: Ability to translate complex business tasks into AI engineering solutions and collaborate directly with client teams (CTOs, AI Leads).
 * Agility: Comfortable navigating fast-moving environments and tuning model workloads for diverse accelerator architectures.
 * Vendor & Strategic Partnership Collaboration: Experience collaborating with customers, model vendors, or ecosystem partners on benchmarking, optimization, finetuning, or launch readiness initiatives.

## Description

* Architect Production-Ready Agentic Frameworks: Design and implement sophisticated multi-agent workflows, autonomous reasoning loops, and tool-augmented LLM architectures capable of resolving complex, real-world customer challenges.
 * Direct Customer Integration: Embed deeply with tech innovators, CTOs, and AI engineering leads to transform ambiguous business requirements into high-performance, deterministic AI/Agentic workflows.
 * Synthesize Research and Deployment: Quickly prototype cutting-edge agentic frameworks-leveraging LangGraph, AutoGen, or custom execution graphs-and harden them for enterprise-scale production and stateful memory retention.
 * Drive Reliability and Evaluation: Develop comprehensive reusable Evals frameworks and safety guardrails to monitor reasoning precision, execution security, latency, and cost-efficiency across agentic systems.
 * Optimize the DigitalOcean Ecosystem: Serve as a strategic feedback link between our customers and core AI/ML Product teams, converting field deployment friction into foundational platform enhancements.
 * Platform Validation & Product Acceleration: Act as the "first customer" for DigitalOcean's AI-native platform capabilities including Inference Engine, runtimes, orchestration systems, GPU platforms, and deployment workflows. Surface real-world operational insights, architectural gaps, and scaling bottlenecks directly to Product Engineering and Research teams.
 * Travel & Collaboration Requirements: Ability to travel up to 30% for customer engagements, strategic workshops, conferences, and internal collaboration.