Conductor AI
Forward Deployed Software Engineer
About this role
A forward-deployed software engineer role blending hands-on coding with direct customer engagement. You'll work onsite with government and defense partners to configure AI-powered software, gather feedback, and drive product improvements while maintaining production code in Python and TypeScript.
What you'll do
- Deploy to customer sites to configure, optimize, and support ConductorAI software with custom workflows
- Write and maintain production-quality code in Python and TypeScript within a small engineering team
- Gather user feedback directly and translate requirements into actionable product improvements
- Debug systems, improve reliability and performance based on real-world customer usage
- Build technical demonstrations for customers and present complex concepts to non-technical stakeholders
- Identify automation opportunities and process improvements at customer sites
What they're looking for
- Python and TypeScript development
- LLMs and modern AI application techniques
- Customer-facing technical communication
- System debugging and performance optimization
- Full-stack development
- High autonomy in ambiguous environments
- DoD Secret clearance (required)
Benefits
- Competitive salary ($150k-$220k base) with meaningful equity
- Real impact on mission-critical workflows
- Access to state-of-the-art technology and novel problems
- Ability to shape role, culture, and product direction as early team member
- Annual merit refreshes based on impact
- Opportunity to work with defense and national security organizations
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Conductor AI
Conductor AI builds AI-powered document processing solutions for government and commercial sectors. The company is hiring forward-deployed software engineers and full stack engineers to configure its platform, gather customer feedback, and develop production code across Python, TypeScript, and web technologies.
View all jobs at Conductor AILikely interview questions
- Tell us about a time you worked directly with end users or customers to understand their needs and translate that feedback into a technical solution. How did you validate that your solution actually addressed their problem?
- Describe your experience with LLMs and modern AI application techniques. What projects have you built or shipped, and what did you learn about their limitations in production?