DigitalOceanListed on Himalayas
Forward Deployed Applied Scientist II (Agentic AI)
Remote · United States
Source: Himalayas. This job was published on Himalayas; you apply there.
$167K–$209K/yrRemoteFull-timeMid levelData Science
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Pay
$167K–$209K/yr
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At a glance
- Education
- PhD
- Industry
- Developer Tools & Cloud
- Benefits mentioned
- Equity / stock options
Skills mentioned
llmmachine learningpythonpytorchdeep learningfastapitensorflow
About the role
Dive in and do the best work of your career at DigitalOcean. Journey alongside a strong community of top talent who are relentless in their drive to build the simplest scalable cloud. If you have a growth mindset, naturally like to think big and bold, and are energized by the fast-paced environment of a true industry disruptor, you’ll find your place here. We value winning together—while learning, having fun, and making a profound difference for the dreamers and builders in the world.
The Forward Deployed Engineering (FDE) team operates at the intersection of AI research, production deployment, and customer impact. As an Agentic AI Applied Scientist, you won't sit in an isolated research lab—you will embed directly with high-growth startups, tech innovators, and AI native enterprise partners. You will design, build, and deploy custom autonomous agent architectures running on DigitalOcean’s high-performance AI infrastructure.
What You’ll Do
- 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.
What You’ll Add to DigitalOcean
- 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.
Preferred Qualifications
- 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.
Compensation Range:
- $167,000 - $209,000
*This is a remote role
JR: 2026-8207
Why You’ll Like Working for DigitalOcean
- We innovate with purpose. You’ll be a part of a cutting-edge technology company with an upward trajectory, who are proud to simplify cloud and AI so builders can spend more time creating software that changes the world. As a member of the team, you will be a Shark who thinks big, bold, and scrappy, like an owner with a bias for action and a powerful sense of responsibility for customers, products, employees, and decisions.
- We prioritize career development. At DO, you’ll do the best work of your career. You will work with some of the smartest and most interesting people in the industry. We are a high-performance organization that will always challenge you to think big. Our organizational development team will provide you with resources to ensure you keep growing. We provide employees with reimbursement for relevant conferences, training, and education. All employees have access to LinkedIn Learning's 10,000+ courses to support their continued growth and development.
- We care about your well-being. Regardless of your location, we will provide you with a competitive array of benefits to support you from our Employee Assistance Program to Local Employee Meetups to flexible time off policy, to name a few. While the philosophy around our benefits is the same worldwide, specific benefits may vary based on local regulations and preferences.
- We reward our employees. The salary range for this position is based on market data, relevant years of experience, and skills. You may qualify for a bonus in addition to base salary; bonus amounts are determined based on company and individual performance. We also provide equity compensation to eligible employees, including equity grants upon hire and the option to participate in our Employee Stock Purchase Program.
- DigitalOcean is an equal-opportunity employer. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.
Application Limit: You may apply to a maximum of 3 positions within any 180-day period. This policy promotes better role-candidate matching and encourages thoughtful applications where your qualifications align most strongly.
Originally posted on Himalayas