
201 - 500 employees
Founded 2004
đŒ Consulting
đŁ Marketing
âïž SaaS
Consulting âą Marketing âą SaaS
Inviso is a Microsoft Cloud Solution Provider (CSP) that specializes in transformative technology solutions tailored for an AI-driven world. With over 20 years of experience as a proven Microsoft partner, Inviso offers a range of services including data analytics, business process automation, cybersecurity, and data governance. Their mission is to help organizations optimize their use of Microsoft technologies to enhance productivity and secure their operations. Inviso leverages advanced AI technologies and provides expert guidance to drive meaningful organizational transformation, ensuring that clients can thrive in a secure, modern work environment.
đ„ 3 minutes ago
Where this job comes from
Posted on Inviso's careers page, not through a job board
First seen by Remote Rocketship 3 minutes ago

201 - 500 employees
Founded 2004
đŒ Consulting
đŁ Marketing
âïž SaaS
Consulting âą Marketing âą SaaS
Inviso is a Microsoft Cloud Solution Provider (CSP) that specializes in transformative technology solutions tailored for an AI-driven world. With over 20 years of experience as a proven Microsoft partner, Inviso offers a range of services including data analytics, business process automation, cybersecurity, and data governance. Their mission is to help organizations optimize their use of Microsoft technologies to enhance productivity and secure their operations. Inviso leverages advanced AI technologies and provides expert guidance to drive meaningful organizational transformation, ensuring that clients can thrive in a secure, modern work environment.
âą Build and operate AI capabilities across an enterprise platform âą Work on agent runtimes, model routing, RAG, tool/function calling, guardrails, evaluation, monitoring, cost management, latency optimization, and production quality controls âą Ship AI capabilities that work in production rather than demos âą Move AI systems from prototype to monitored production systems âą Evaluate AI behavior rigorously âą Partner with product and engineering teams to determine when AI is and is not the right solution âą Turn experiments into production features âą Build evaluation discipline into the delivery process âą Help client teams make informed decisions about where AI creates real value âą Deliver AI capabilities that are useful, reliable, measurable, safe, and cost aware
âą Experience shipping software backed by LLMs, ML models, RAG systems, or agentic workflows to real production users âą Experience designing or implementing agent runtime, orchestration, model routing, tool/function calling, or AI workflow patterns âą Strong understanding of RAG, grounding, retrieval quality, prompt design, context management, and evaluation approaches âą Experience building evaluation harnesses, golden sets, regression checks, quality gates, or measurable AI performance frameworks âą Ability to treat cost, latency, reliability, and safety as first-class engineering constraints âą Experience building guardrails and controls for AI systems, including untrusted retrieved content, tool output risk, and failure modes âą Experience monitoring production AI behavior and improving systems based on evidence âą Strong software engineering skills and ability to collaborate with backend, platform, product, and security teams âą Strong communication and collaboration skills for client-facing consulting environments âą Pragmatic mindset with the ability to prioritize business value and ship useful AI capabilities quickly and responsibly âą Desired: Experience with Claude, GPT, Azure OpenAI, open-source models, model routing, fine-tuning, distillation, or small/edge models âą Desired: Experience with MCP, A2A, multi-agent orchestration, AI tool calling, or agent evaluation âą Desired: Experience with LLM-as-judge approaches calibrated against human evaluation âą Desired: Experience with semantic knowledge management, ontologies, knowledge graphs, or semantic layers âą Desired: Experience with AI development lifecycle practices across data, build, evaluation, deployment, monitoring, and continuous improvement âą Desired: Experience using AI-assisted development tools while maintaining strong review, testing, and safety discipline
âą Direct-hire permanent employee position âą Remote work arrangement
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