AI/Data Solutioning Engineer

ProArch is seeking an experienced Senior AI Engineer to lead the design and development of AI/Data solutions, services, and reusable accelerators. This role is engineering-first, with approximately 50–75% of time focused on building solutions and 25–50% supporting presales activities including discovery, architecture definition, and client interactions. The ideal candidate will combine strong hands-on engineering expertise with solution architecture capability, with a focus on AI agents and modern data platforms. Responsibilities: Lead development of AI/Data solutions, accelerators, and reusable service offerings Design and implement production-grade PoCs, MVPs, and scalable frameworks Architect end-to-end solutions across data pipelines, storage, semantic models, and AI layers Develop AI agents using Azure AI Foundry including orchestration, tool integration, and grounding Implement advanced AI patterns including RAG and multi-agent workflows Ensure solutions are scalable, secure, and governed (RBAC, monitoring, evaluation) Drive reusable solution patterns and internal IP creation Collaborate with delivery teams to transition solutions into production Support pre-sales activities including workshops, proposals, and demos Communicate solution value to both technical and business stakeholders Strong experience in Data Engineering, AI Engineering, or Full-Stack Engineering Expertise in Python/.Net, SQL, and distributed systems (Spark preferred) Experience building large-scale data platforms and pipelines Hands-on experience with Azure Data + AI ecosystem (Fabric, Synapse, Databricks) Experience with LLMs, embeddings, vector search, and RAG architecture. Experience with agent orchestration frameworks such as Semantic Kernel or LangChain or similar. Strong solution architecture and design thinking capability Expertise of observability practices including Application Insights/OpenTelemetry. Ability to communicate clearly in written and verbal form; comfortable presenting technical concepts to technical and non-technical audiences. Ability to translate business problems into scalable technical solutions Strong analytical and problem-solving abilities Stakeholder management and collaboration skills Proactive, self-driven, and customer-focused mindset Preferred Qualifications: Microsoft Fabric experience (Lakehouse, OneLake concepts, semantic models). Experience with CI/CD for data/AI workloads and basic MLOps/LLMOps practices. Understanding of identity and access management patterns (Entra ID, managed identities, service principals). Exposure to Agent evaluation frameworks.