Forward Deployed Applied Scientist II (Agentic AI)

digitalocean98; United States; Hybrid; USD 167,000 - 209,000; Full time

Benefits offered by this job

Flexible time off

Learning resources

Conferences support

Equity

Job summary

digitalocean98 is seeking an experienced Applied AI Engineer to build and deploy multi-agent workflows for customers. You will prototype, productionize, evaluate, and feed back into AI infrastructure teams to shape dependable AI products.

You will design tool-enabled language model systems, collaborate with customer leaders, and translate challenges into scalable solutions across inference, runtimes, and GPU deployment. This role requires travel up to 30%.

Qualifications

• 6+ years hands-on experience in applied AI, ML, or data science.
• Experience with multi-agent orchestration, tool use, function calling, structured outputs, dynamic planning, and persistent memory.
• Strong production Python skills with Pydantic, FastAPI, asyncio, and PyTorch.
• Clear technical communication for engineering and executive audiences.
• Willingness to travel up to 30% for customer work, workshops, conferences, and internal collaboration.

Responsibilities

• Design multi-agent workflows, reasoning loops, and tool-enabled language model systems for real customer problems.
• Work with customer technical leaders to clarify requirements and shape dependable AI solutions.
• Prototype agent frameworks and harden them for production use, including systems with persistent state or memory.
• Create reusable evaluations and safety controls to measure accuracy, security, latency, and cost.
• Translate deployment challenges and customer feedback into improvements for AI and ML products.
• Validate platform capabilities across inference, runtimes, orchestration, GPU infrastructure, and deployment workflows; report gaps and scaling issues to product, engineering, and research teams.

Skills

Multi-agent orchestration

Tool use / function calling

Structured outputs

Dynamic planning

Persistent memory

Production Python

Education

Master’s degree

PhD

Tools

Pydantic

FastAPI

asyncio

PyTorch

Job description

Role overview

Build and deploy applied AI systems for customers by turning complex business needs into reliable agentic workflows. This customer-facing role spans prototyping, production engineering, evaluation, and feedback to teams developing AI infrastructure and products.

Responsibilities

• Design multi-agent workflows, reasoning loops, and tool-enabled language model systems for real customer problems.
• Work with customer technical leaders to clarify requirements and shape dependable AI solutions.
• Prototype agent frameworks and harden them for production use, including systems with persistent state or memory.
• Create reusable evaluations and safety controls to measure accuracy, security, latency, and cost.
• Translate deployment challenges and customer feedback into improvements for AI and machine learning products.
• Validate platform capabilities across inference, runtimes, orchestration, GPU infrastructure, and deployment workflows; report gaps and scaling issues to product, engineering, and research teams.

Requirements

• At least six years of hands-on experience in applied AI, machine learning, or data science.
• Demonstrated experience with multi-agent orchestration, tool use or function calling, structured outputs, dynamic planning, and persistent memory.
• Strong production Python skills, including experience with tools such as Pydantic, FastAPI, asyncio, and PyTorch.
• Clear technical communication and the ability to explain AI trade-offs to engineering and executive audiences.
• Willingness to travel up to 30% for customer work, workshops, conferences, and internal collaboration.

Nice to have

• A master’s degree or PhD in a relevant technical field; experience with deep learning frameworks, distributed training, agent frameworks, transformers, or state space models; research contributions such as publications or patents; and experience working with customers, model vendors, or ecosystem partners on benchmarking, optimization, fine-tuning, or launch readiness.

Benefits and work setup

The role is described as hybrid. The listed base salary range is $167,000-$209,000; eligible employees may also receive a bonus and equity. Benefits vary by location and include flexible time off, employee assistance, learning resources, and support for relevant training or conferences.