Senior Software Engineer - AI Tools Lead (TS/SCI)

Bitwise; Laurel (MD); On-site; USD 282,000 - 332,000; Full time

Benefits offered by this job

Top salaries

PTO 3–5 weeks

11 federal holidays

Education assistance

401(k) match

Employer-paid insurance

Job summary

Bitwise seeks a Senior Software Engineer to lead the development of AI tools and applications critical to national security missions. You’ll architect, build, and mentor while collaborating with customers to translate requirements into robust technical solutions.

You’ll own reliability, security, and performance across AI tools, engage with multiple teams, and guide governance, tooling, and best practices to advance our AI infrastructure and product readiness.

Qualifications

• 12 years of software engineering experience, or a BS in a technical discipline plus 8+ years
• Mastery of Python
• Production software development
• Experience with Large Language Models (LLMs) in code workflows
• Expertise in UI/UX principles
• Cloud experience with AWS or equivalent
• Kubernetes/Helm
• Argo CD or CI/CD frameworks
• SRE best practices for production systems
• Docker and containerization
• Experience with OpenWebUI or LLM UI open-source tools
• Experience with customer requirements elicitation and community outreach

Responsibilities

• Develop and maintain high-quality AI tools and applications
• Lead AI Tools and Applications initiatives across teams
• Mentor junior developers and coach engineering discipline
• Engage with customers to translate needs into technical solutions
• Establish governance and technical policies for engineering teams
• Oversee monitoring, logging, and observability for AI services
• Ensure reliability, security, and performance of components

Job description

Bitwise seeks a Senior Software Engineer to lead the development of AI tools and applications critical to national security missions. You’ll architect, build, and mentor while collaborating with customers to translate requirements into robust technical solutions.

You’ll own reliability, security, and performance across AI tools, engage with multiple teams, and guide governance, tooling, and best practices to advance our AI infrastructure and product readiness.