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Inviso

Applied AI Engineer

Inviso

. Build and operate AI capabilities across an enterprise platform .

Posted 11/4/2026full-timeRemote • MexicoMid-LevelSeniorWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in building and operating AI capabilities, with a strong focus on production quality controls, evaluation frameworks, and collaboration with cross-functional teams. Proficient in managing AI systems' cost, latency, and reliability while ensuring safety and effectiveness in real-world applications.

Highest-signal resume keywords
Experience Shipping Software Backed By LLMsStrong Understanding Of RAG And Evaluation ApproachesExperience Building Evaluation Harnesses And Quality GatesExperience Monitoring Production AI BehaviorStrong Software Engineering Skills

ATS Keywords

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Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills
Agent Runtime DevelopmentModel RoutingTool/Function CallingAI Workflow PatternsEvaluation FrameworksCost ManagementLatency OptimizationGuardrails For AI SystemsAI Development Lifecycle PracticesPrompt Design
Soft Skills
Strong Communication SkillsCollaboration SkillsPragmatic Mindset
Tools & Technologies
ClaudeGPTAzure OpenAIOpen-Source ModelsMCPA2AMulti-Agent OrchestrationAI Tool CallingAI-Assisted Development ToolsSemantic Knowledge Management
Industry Keywords
AI CapabilitiesProduction EnvironmentsEvaluation DisciplineClient-Facing ConsultingMeasurable AI Performance

Tech Stack

Tools & technologies
Azure

About the role

Key responsibilities & impact
  • 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 environments
  • Evaluate AI behavior rigorously
  • Partner with product and engineering teams to determine when AI is the right solution
  • Turn experiments into production features
  • Build evaluation discipline into the delivery process
  • Help client teams make informed decisions about where AI creates real value

Requirements

What you’ll need
  • 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

Benefits

Comp & perks
  • Remote work arrangement
  • Permanent direct-hire employee position
  • Opportunity to work with a global multi-billion dollar software conglomerate
  • Client-facing consulting environment