Senior Software Development Engineer III

The Senior Software Development Engineer III will support the GRACE Development Team by designing, building, and maintaining the cloud infrastructure and backend platforms that power ARPA-H’s production AI assistant. This position leads the development of scalable, secure, and highly available agentic AI infrastructure while driving innovation across cloud architecture, AI orchestration, production operations, and software engineering best practices., * Design, develop, and maintain the cloud infrastructure supporting GRACE using Microsoft Azure services including Azure Functions, Azure API Management, Azure Container Apps, and Azure OpenAI Service.

• Develop and maintain scalable backend services, APIs, data pipelines, vector databases, and document indexing systems supporting enterprise AI applications.
• Design and implement Retrieval-Augmented Generation (RAG) pipelines, semantic search capabilities, embeddings, and document ingestion workflows.
• Develop and maintain multi-agent AI orchestration, Model Context Protocol (MCP) services, tool-calling frameworks, and Agent-to-Agent (A2A) communication capabilities.
• Build highly available, secure, and resilient backend systems utilizing modern distributed system architecture and cloud-native design principles.
• Develop and maintain Infrastructure as Code (IaC), CI/CD pipelines, automated deployments, and release management processes.
• Implement authentication, authorization, identity management, and secure access controls utilizing Microsoft Entra ID and modern authentication standards.
• Develop observability solutions including monitoring, logging, distributed tracing, performance metrics, alerting, and incident response capabilities.
• Monitor AI platform utilization, token consumption, cloud resource usage, and operational costs while optimizing platform performance and efficiency.
• Implement reliability engineering practices including fault tolerance, graceful degradation, retry mechanisms, circuit breakers, and disaster recovery capabilities.
• Collaborate with front-end developers, product managers, researchers, and UX designers to deliver high-quality AI-powered solutions.
• Mentor software engineers while establishing engineering standards, architecture patterns, testing strategies, and code quality practices.
• Ensure compliance with federal cybersecurity, privacy, responsible AI, and cloud security requirements.
• Participate in architecture reviews, Agile ceremonies, technical planning, and strategic engineering initiatives.

• Bachelor’s degree in Computer Science, Software Engineering, Information Technology, or a related discipline; Master’s degree preferred or equivalent practical experience.
• Minimum of seven (7) years of professional software engineering experience developing and supporting enterprise backend systems.
• Extensive experience developing applications using Python and at least one additional backend programming language.
• Demonstrated expertise designing and deploying cloud-native applications on Microsoft Azure.
• Experience with Azure Functions, Azure API Management, Azure Container Apps, Azure OpenAI Service, and related Azure services.
• Strong experience with distributed systems, APIs, microservices, asynchronous programming, and cloud architecture.
• Experience building production AI applications utilizing LLMs, Retrieval-Augmented Generation (RAG), semantic search, vector databases, embeddings, and tool-calling frameworks.
• Experience implementing CI/CD pipelines, Infrastructure as Code (Terraform, Bicep, or similar), and DevSecOps practices.
• Experience with containerization technologies including Docker and Kubernetes.
• Strong understanding of authentication technologies including OAuth2, OpenID Connect, and Microsoft Entra ID.
• Experience supporting production systems, monitoring, incident response, and operational excellence.
• Familiarity with Model Context Protocol (MCP), Agent-to-Agent (A2A) architectures, and multi-agent AI systems is highly desirable.
• Strong analytical, problem-solving, and troubleshooting skills.
• Excellent written and verbal communication skills with the ability to explain complex technical concepts to technical and non-technical audiences.
• Demonstrated ability to lead engineering initiatives and mentor technical teams in a collaborative Agile environment.