AI Field Developer

QuilrAI is hiring an AI Field Developer to implement and customize its AI security solutions for customers. The role builds production-quality integrations, troubleshoots deployments, and translates customer requirements and field feedback into reliable technical solutions and product improvements.

What you'll do:

• Build Customer Integrations: Develop and maintain Python-based integrations, APIs, SDKs, adapters, and connectors for enterprise AI applications and infrastructure
• Integrate Quilr's security capabilities into LLM-powered applications, AI agents, orchestration frameworks, and MCP-based workflows
• Build proof-of-concept implementations and turn successful prototypes into reliable, maintainable solutions
• Deploy and Customize AI Security Solutions: Implement Quilr within customer environments, including cloud infrastructure, containerized workloads, and enterprise application stacks
• Configure integrations with customer identity systems, logging platforms, API gateways, and security tools; support on-premises, private-cloud, and hybrid deployments where applicable
• Troubleshoot Real-World Engineering Challenges: Debug API, authentication, networking, configuration, and runtime issues
• Investigate AI-specific security challenges such as prompt injection, unsafe tool execution, insecure agent permissions, and untrusted context
• Develop test cases and reproducible examples to identify integration gaps and improve reliability
• Collaborate with Customers and Product Engineering: Work with customer developers, DevOps teams, and security engineers to understand implementation requirements
• Translate field problems into actionable engineering issues, product enhancements, and reusable integration patterns
• Improve Engineering Quality: Write unit tests, integration tests, and deployment automation; follow secure coding practices and contribute to reusable code and technical documentation

What they're looking for:

• Approximately 1–4 years of experience in software engineering, backend development, AI engineering, DevOps, or a related technical field; strong early-career candidates are encouraged to apply
• Strong hands-on programming skills in Python and familiarity with REST APIs, JSON, authentication, and common software engineering practices
• Experience building or integrating applications that use LLMs, AI agents, or modern AI development frameworks
• Familiarity with Git, Linux, debugging, testing, and basic CI/CD workflows
• Understanding of application deployment concepts, including Docker, cloud environments, environment configuration, and application logging
• Ability to troubleshoot unfamiliar systems and work independently in ambiguous environments
• Strong communication skills and willingness to collaborate directly with enterprise customers
• Candidates must possess active, valid US work authorization
• Quilr is currently unable to provide visa sponsorship
• Experience with LangChain, LangGraph, LlamaIndex, or comparable AI orchestration tools
• Familiarity with MCP servers, clients, tools, and integration patterns
• Exposure to AWS, Azure, GCP, Kubernetes, or private-cloud deployments