Salary
≈ $21k – $57k per year (Estimated)
Location
Remote (Canada)
Employment
Full-Time
First seen by Alion on Sep 25, 2026.
Overview
Company
Impact
Profile match
Applied AI Engineer
This is a remote, client-facing consultant role with Inviso. In this position, you will support an external software development organization as part of Inviso's delivery team, helping build production AI capabilities that customers can rely on in real operational workflows.
The Inviso Applied AI Engineer is responsible for building and operating AI capabilities across an enterprise platform, including agent runtimes, model routing, RAG, tool/function calling, guardrails, evaluation, monitoring, cost management, latency optimization, and production quality controls.
This role is focused on shipping AI that works in production, not demos. The ideal candidate understands how to move from prototype to monitored production systems, can evaluate AI behavior rigorously, and can partner with product and engineering teams to decide when AI is the right solution and when it is not.
This is a 100% remote role but may require some travel due to client needs.
Experience & Skills Required
Success in this role is measured by the ability to deliver AI capabilities that are useful, reliable, measurable, safe, and cost aware. Applied AI Engineers are expected to turn experiments into production features, build evaluation discipline into the delivery process, and help client teams make informed decisions about where AI creates real value.
Benefits
In addition to the base pay, Inviso provides an annual $2,000 training allowance to all of its employees, plus paid time off, paid holidays, and other benefits.
Why Inviso
This is a remote, client-facing consultant role with Inviso. In this position, you will support an external software development organization as part of Inviso's delivery team, helping build production AI capabilities that customers can rely on in real operational workflows.
The Inviso Applied AI Engineer is responsible for building and operating AI capabilities across an enterprise platform, including agent runtimes, model routing, RAG, tool/function calling, guardrails, evaluation, monitoring, cost management, latency optimization, and production quality controls.
This role is focused on shipping AI that works in production, not demos. The ideal candidate understands how to move from prototype to monitored production systems, can evaluate AI behavior rigorously, and can partner with product and engineering teams to decide when AI is the right solution and when it is not.
This is a 100% remote role but may require some travel due to client needs.
Experience & Skills Required
- 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, not opinion.
- 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.
Success in this role is measured by the ability to deliver AI capabilities that are useful, reliable, measurable, safe, and cost aware. Applied AI Engineers are expected to turn experiments into production features, build evaluation discipline into the delivery process, and help client teams make informed decisions about where AI creates real value.
Benefits
In addition to the base pay, Inviso provides an annual $2,000 training allowance to all of its employees, plus paid time off, paid holidays, and other benefits.
Why Inviso
- Our Culture & Values are who we are.
- Our commitment to excellence is interwoven with the way we care about our people. Our low attrition rate, high average employee tenure, and the number of people that have been with Inviso for 10, 15, even 20 years, speaks volumes to who we are as a company.
- We are a meritocracy through and through. Those who excel, grow. There is no ceiling, we don't tolerate politics.
- Inviso has maintained a deep, well-established relationship with Microsoft for over 20 years. We are a top-rated supplier and are proud to be a Managed Partner with many credentials.
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