Software Engineer

Blueprint is a technology solutions firm that helps organizations connect strategy and execution across AI, cloud, data, product development, and emerging technology. The Software Engineer will build applied AI and platform solutions, develop agentic workflows and integrations, and convert prototypes into secure, observable, production-ready services while collaborating with stakeholders and end users.

Responsibilities:

• Identify high-friction operational workflows, quantify the current-state cost, and design automated or agent-driven solutions that improve efficiency, reduce errors, and increase throughput
• Build AI agents and intelligent workflows using Azure AI Foundry, Copilot Studio, Microsoft Agent Framework, MCP, and related frameworks
• Design multi-step tool use, orchestration, and human-in-the-loop workflows for agentic applications
• Replatform prototypes and proofs of concept into secure, scalable, observable, and supportable production services
• Design and develop RESTful APIs, tool/function endpoints, and backend services using Azure App Services
• Apply prompt engineering, grounding, retrieval, Azure AI Search, and evaluation practices to improve AI system quality and reliability
• Build evaluation and quality infrastructure for AI systems, including offline evaluation sets, CI regression gates, drift detection, and release criteria
• Develop observability for AI and agentic systems, including quality, cost, latency, tool-call outcomes, and rollback capabilities
• Build integrations between internal and external systems while maintaining appropriate human review, approval, and intervention points
• Implement secure authentication and authorization using Entra ID, including workload identity, least-privilege access, and delegated permissions
• Support privacy, security, accessibility, responsible AI, and compliance assessments for AI-powered solutions
• Use Azure DevOps for source control, CI/CD, automated testing, release management, and work tracking
• Partner with engineers, program managers, stakeholders, and end users to understand operational processes and translate them into effective technical solutions
• Participate in code reviews, unit testing, Agile ceremonies, troubleshooting, and debugging across distributed and AI-dependent systems
• Evaluate emerging AI and agent technologies and provide practical recommendations for their application
• Document workflow architectures, agent behavior and boundaries, integration contracts, and system designs

Requirements:

• Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent professional experience
• 3+ years of professional software development experience, with a focus on cloud-based applications
• Strong proficiency with .NET, C#, Python, and SQL for backend development
• Hands-on experience building with LLMs and AI services , including prompt engineering
• Experience taking at least one AI-powered feature, agent, or automation into production or near-production and being able to discuss the technical implementation in depth
• Demonstrated experience automating real-world workflows through process automation, orchestration, integrations, or agentic tooling
• Strong knowledge of Azure App Services, Azure SQL, Logic Apps, Copilot Studio, Azure AI Foundry, and Azure AI Search
• Experience using Azure DevOps for version control, build automation, release management, and project tracking
• Experience designing secure applications using Entra ID for authentication and authorization
• Strong understanding of SQL database design, optimization, and querying
• Strong problem-solving, debugging, and troubleshooting abilities across code, data, configuration, and AI/model behavior
• Ability to collaborate effectively with both technical and non-technical stakeholders
• Ability to work directly with end users, gather requirements, provide technical guidance, and iterate based on feedback
• Prior experience with the client's organization and familiarity with its development practices, technologies, and internal systems
• Experience with agent frameworks and orchestration, such as Microsoft Agent Framework, Semantic Kernel, LangGraph, or MCP
• Experience with tool design and multi-agent coordination
• Experience developing LLM evaluation harnesses , including offline evaluation sets, LLM-as-judge approaches, and automated quality gates
• Demonstrated ability to take an internal prototype, hack, or proof of concept and turn it into a supported production service
• Experience replacing legacy manual processes through automation, particularly where organizational workflows are complex
• Front-end development experience with React
• Experience with large-scale distributed systems and multiple integration points
• Familiarity with responsible AI practices and enterprise compliance review processes