Forward Deployed Engineer

• 1-4 years of software engineering, AI engineering, data engineering, or related experience
• Strong Python skills
• Experience working with APIs, databases, and data pipelines
• Familiarity with cloud platforms such as AWS, Azure, or Google Cloud
• Experience with modern AI/LLM tools, APIs, or frameworks
• Understanding of retrieval, tool use, agents, or similar AI application patterns
• Ability to work with both structured and unstructured data
• Strong debugging and problem-solving skills
• Comfortable working directly with customers and technical professionals
• Ability to translate real-world needs into working technical solutions
• Curiosity, adaptability, and comfort operating in an early-stage environment

Nice to have

• Experience building or deploying generative AI applications
• Experience with AI evaluation, observability, verification, or human-in-the-loop systems
• Familiarity with geospatial technologies, GIS, satellite imagery, or spatial data
• Experience with infrastructure, engineering, environmental, field, or other technical workflows
• Experience supporting pilots or deploying software directly with customers
• Familiarity with frontend or full-stack development

We’re looking for someone early in their career who wants broad exposure and significant hands-on responsibility. You should be comfortable moving between code, data, product questions, and customer conversations, and excited by the opportunity to help shape both the technology and how we bring it into the field.

This is a hybrid position based in Annapolis, Maryland, with an expectation of working at least three days a week onsite at the bAI Labs in the historic Livery Building., * strong debugging and problem solving skills: 2 years (Required)

Pulled from the full job description

• 401(k)
• Health insurance
• 401(k) matching
• Vision insurance
• Dental insurance
• Life insurance, * 401(k)
• 401(k) matching
• Dental insurance
• Health insurance
• Life insurance
• Vision insurance

We’re looking for an early-career Forward Deployed Engineer to help us build, test, and deploy our emerging applied AI platforms in real-world settings. This is a hands-on role for someone who enjoys building technology, solving problems with users, and helping shape products at an early stage.

Because we are still a small team, this person will have meaningful responsibility from the start. You’ll work closely with our founders, product lead, technical professionals, research collaborators, and Frontier Partners as our platforms move from beta into real-world pilots and early adoption. The role will involve both product development and customer-facing deployment.

You’ll spend time understanding how Frontier Partners actually work, configuring and integrating our technology for specific use cases, testing it with real data, troubleshooting issues, and bringing what you learn back into the product. Depending on the project, you may work with geospatial data, technical documents, field observations, images, structured datasets, or other sources that need to be brought together within an AI-enabled workflow.

The technical work may include AI workflows and agents, APIs, data integration, retrieval, evaluation, verification, and deployment. We are not looking for someone who only wants to work on isolated research problems. This role is about helping turn emerging AI capabilities into practical tools that can work reliably in real-world professional environments.

A key part of the job is customer-facing. You’ll work directly with Frontier Partners and technical professionals to understand their workflows, support pilots, help resolve technical challenges, evaluate how the system is performing, and identify where the technology needs to improve.

Because we build AI for real-world professional use, we care about more than whether something works in a demo. Traceability, evaluation, verification, and human review are important parts of how we think about product development.

What you’ll work on

• Building and improving applied AI features and workflows
• AI agents, LLM integrations, APIs, and data pipelines
• Integrating structured and unstructured data into our platforms
• Supporting deployment and configuration for Frontier Partner pilots
• Working directly with users to understand technical requirements and workflows
• Testing, evaluating, and troubleshooting AI behavior
• Helping develop approaches for verification, traceability, and human review
• Turning lessons from real-world use into improvements to the product
• Working across product, technical, and customer-facing needs in a small startup environment