Applied AI Engineer
Inviso is partnering with one of our clients to find an experienced Backend / Platform Engineer to join their team working remotely. Inviso is managing the recruitment and placement process for this opportunity. This is a remote, direct-hire permanent employee position for our client that is a global multi-billion dollar software conglomerate.
The 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.
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.
Desired Qualifications
- 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 Criteria
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.
Skills Required
- Experience shipping software backed by LLMs, machine learning models, RAG systems, or agentic workflows to production users.
- Experience designing or implementing agent runtimes, 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 engineering constraints.
- Experience building guardrails and controls for AI systems, including retrieved content, tool output risks, 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 in client-facing consulting environments.
- Pragmatic mindset focused on prioritizing business value and shipping useful AI capabilities 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 review, testing, and safety discipline.
What We Do
Inviso Corporation is a global technology consulting firm based in Bellevue, Washington. The company specializes in helping organizations optimize security, performance, and digital decision-making by combining expertise in AI, data, marketing, and sales enablement. Their services include application development, business intelligence, and software asset management, catering to a diverse range of clients from small businesses to large enterprises.
