
201 - 500 employees
Founded 2004
đź Consulting
đŁ Marketing
âď¸ SaaS
Consulting ⢠Marketing ⢠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.
đĽ 0 minutes ago
đşđ¸ United States â Remote
â° Full Time
đĄ Mid-level
đ Senior
đ¤ AI Engineer
đŚ H1B Visa Sponsor
đť Ghost score 10%
Where this job comes from
Posted on Inviso's careers page, not through a job board
First seen by Remote Rocketship 0 minutes ago

201 - 500 employees
Founded 2004
đź Consulting
đŁ Marketing
âď¸ SaaS
Consulting ⢠Marketing ⢠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.
⢠Build and operate AI capabilities across an enterprise platform ⢠Develop agent runtimes, model routing, RAG, tool/function calling, guardrails, evaluation, monitoring, cost management, latency optimization, and production quality controls ⢠Ship AI capabilities that work reliably in production rather than demos ⢠Move AI systems from prototype to monitored production systems ⢠Evaluate AI behavior rigorously ⢠Partner with product and engineering teams to determine when AI is appropriate and when it is not ⢠Turn experiments into production features ⢠Build evaluation discipline into the delivery process ⢠Help client teams make informed decisions about where AI creates real value ⢠Deliver AI capabilities that are useful, reliable, measurable, safe, and cost aware
⢠Experience shipping software backed by LLMs, ML models, RAG systems, or agentic workflows to real production users ⢠Experience designing or implementing agent runtime, orchestration, model routing, tool/function calling, or AI workflow patterns ⢠Strong understanding of RAG, grounding, retrieval quality, prompt design, context management, and evaluation approaches ⢠Experience building evaluation harnesses, golden sets, regression checks, quality gates, or measurable AI performance frameworks ⢠Ability to treat cost, latency, reliability, and safety as first-class engineering constraints ⢠Experience building guardrails and controls for AI systems, including untrusted retrieved content, tool output risk, and failure modes ⢠Experience monitoring production AI behavior and improving systems based on evidence ⢠Strong software engineering skills and ability to collaborate with backend, platform, product, and security teams ⢠Strong communication and collaboration skills for client-facing consulting environments ⢠Pragmatic mindset with the ability to prioritize business value and ship useful AI capabilities quickly and responsibly ⢠Experience with Claude, GPT, Azure OpenAI, open-source models, model routing, fine-tuning, distillation, or small/edge models ⢠Experience with MCP, A2A, multi-agent orchestration, AI tool calling, or agent evaluation ⢠Experience with LLM-as-judge approaches calibrated against human evaluation ⢠Experience with semantic knowledge management, ontologies, knowledge graphs, or semantic layers ⢠Experience with AI development lifecycle practices across data, build, evaluation, deployment, monitoring, and continuous improvement ⢠Experience using AI-assisted development tools while maintaining strong review, testing, and safety discipline
⢠Remote work ⢠Permanent employee position ⢠Direct-hire employment ⢠Opportunity to work with a global multi-billion dollar software conglomerate
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