AI Solutions Architect

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Upstart 13

WebsiteLinkedInAll Job Openings

51 - 200 employees

A software development company with the talent, the culture, and the process to deliver on the promise of outsourcing. Our teams are invested in solving your issues and reaching your goals.

📋 Description

• Own the end-to-end AI architecture across LLM orchestration, retrieval, enterprise data integration, and deployment. • Define architectural standards, best practices, and reusable AI patterns across the platform. • Evaluate architectural trade-offs involving latency, cost, model quality, scalability, security, and maintainability. • Define the long-term AI strategy in collaboration with the Delivery Lead and engineering leadership. • Design intelligent agent architectures, including tool calling, retrieval, planning, multi-step reasoning, and state management. • Design AI integrations with enterprise data platforms, semantic models, APIs, and knowledge repositories. • Define AI evaluation strategies covering quality, hallucination detection, grounding, latency, and cost optimization. • Design observability and monitoring capabilities for AI applications, including prompt performance, model behavior, and operational telemetry. • Collaborate with cloud infrastructure and security teams to ensure secure, resilient, and compliant deployments. • Contribute directly to proof-of-concepts and critical implementation efforts when needed.

🎯 Requirements

• 10+ years of professional experience in software engineering, including designing and architecting enterprise software solutions. • 3+ years of experience designing and delivering production AI solutions leveraging Large Language Models. • Strong experience designing enterprise AI systems using Retrieval-Augmented Generation (RAG), agentic AI, tool calling, prompt orchestration, and multi-agent workflows. • Hands-on experience with Python and modern backend frameworks such as FastAPI or equivalent. • Experience with Azure AI services, including Azure AI Foundry, Azure AI Search, Azure OpenAI, or equivalent AI platforms. • Experience building AI applications using frameworks such as Semantic Kernel, AutoGen, Microsoft Agent Framework, LangGraph, LangChain, or similar orchestration frameworks. • Strong understanding of enterprise data integration, APIs, vector databases, semantic search, and knowledge management architectures. • Experience designing AI evaluation, monitoring, observability, and governance strategies. • Strong understanding of Azure architecture and cloud-native application design. • Experience implementing CI/CD pipelines and Infrastructure-as-Code. • Familiarity with cloud security, identity management, RBAC, and enterprise governance principles.

🏖️ Benefits

• 20+ Paid time off days