AI Engineer
4 days ago
Description Veriforce is seeking a software engineer with hands‑on experience building AI agents and/or working with the Model Context Protocol (MCP). You will join a growing team of talented front‑end, back‑end, QA, and DevOps engineers to expand our platforms to integrate with LLMs, APIs, and enterprise data. Your work will help shape the way our clients and contractors get to work faster, stay compliant, and come home safely every day. What that means day‑to‑day Participate as an integral member of a cross‑functional full‑stack team using agile methodologies. Work in an Agile‑based SDLC that embraces transparency, cooperation, decomposing work, and rapid iteration. Design and develop AI agents capable of reasoning, planning, and taking multi‑step actions to support user journeys/workflows. Build and extend MCP servers/clients for structured, interoperable AI integrations. Integrate models with application APIs, databases, and third‑party tools. Break complex features into manageable, reviewable, shippable pieces. Communicate clearly with engineers about implementation choices, design considerations, performance impacts, and testability. Explain to non‑engineers how technology solves business needs, including demonstrating features for feedback. Methodically debug problems to resolve issues at the root. Review pull requests constructively and receive feedback on your own. Produce code that adheres to coding standards of consistency, readability, testability, security, and maintainability; leverage AI coding assistance (e.g., Copilot). Write meaningful, efficient tests for important parts of an application. What you’ll need to be successful 3 to 5+ years of development experience (C#, Python, TypeScript, Go, or similar). Hands‑on experience building LLM‑based agents or orchestrators. Familiarity with MCP concepts: context servers, standardization tool integration, and protocol‑based communication. Strong understanding of APIs, distributed systems, and cloud‑native architectures. Experience with prompt engineering, embeddings, and retrieval‑augmented generation (RAG). Familiarity with containerization technologies such as Docker, Kubernetes, Rancher, etc. Knowledge of contemporary engineering tools: project boards (JIRA), source control (GitHub, Bitbucket), package managers, build systems, etc. Experience with, or a disposition to embrace, AI‑assisted coding practices. What you’ll get in return We want you to be able to do your best work here. We emphasize providing many ways to support our team to do their best work and believe that if you look after your people, they look after everything else. Personal Health & Wellbeing
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