Forward Deployed Engineer ( Python) | Hybrid

Crossing Hurdles; Washington; On-site; USD 200,000 - 350,000; Full time

Job summary

Crossing Hurdles seeks a highly autonomous Python engineer to build agentic AI systems for U.S. Government missions, from prototype through production.

You will design and integrate LLM applications, including multi-agent systems and human-in-the-loop autonomy, and collaborate with government partners to translate mission needs into scalable technical solutions. This remote, full-time role offers deep ownership of data pipelines, model inference infrastructure, and security considerations, with

Qualifications

• Independently operate in ambiguous, partner-facing settings with technical ownership.
• Strong Python engineer with end-to-end ownership experience.
• Experience with LLMs and creating agentic systems.
• Built or maintained data pipelines or ML infrastructure.
• Familiar with RL workflows or simulation environments.
• Comfortable in high-security or high-reliability environments.

Responsibilities

• Build and deploy agentic AI systems supporting U.S. Government missions from prototype to production.
• Design and integrate LLM applications, including multi-agent systems and human-in-the-loop autonomy.
• Work with government partners to translate mission needs into technical systems.
• Build and maintain large-scale data curation and evaluation pipelines for model training.
• Develop infrastructure for model inference, experimentation, evaluation, and deployment.
• Own systems across the full lifecycle, including discovery, architecture, implementation, and security.

Skills

Python

LLMs

Agent-based systems

Data pipelines

Job description

Type: Full-time

Compensation: $200K - $350K/yr

Location: Remote

Commitment: 10-40 hrs/week

Role Responsibilities

• Build and deploy agentic AI systems supporting U.S. Government missions from prototype to production.
• Design and integrate LLM applications, including multi-agent systems and human-in-the-loop autonomy.
• Work with government partners to translate mission needs into technical systems.
• Build and maintain large-scale data curation and evaluation pipelines for model training.
• Develop infrastructure for model inference, experimentation, evaluation, and deployment.
• Own systems across the full lifecycle, including discovery, architecture, implementation, and security.

Requirements

• Operate independently in ambiguous, partner-facing settings with technical and operational ownership.
• Strong Python engineer with end-to-end ownership experience.
• Experience with LLMs and creating agentic systems.
• Built or maintained data pipelines or ML infrastructure.
• Familiar with RL workflows or simulation environments.
• Comfortable in high-security or high-reliability environments.