AI Engineer
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Job Description
Applied AI Engineer building reliable, evaluated, and monitored production AI systems for Inviso’s enterprise clients. Remote consulting across LLMs, RAG, agents, guardrails, and platform operations.
Responsibilities:
- Support an external software development organization as part of Inviso’s delivery team.
- Build and operate AI capabilities across an enterprise platform.
- Implement agent runtimes, model routing, RAG, tool/function calling, guardrails, evaluation, monitoring, cost management, latency optimization, and production quality controls.
- Move AI solutions from prototype to monitored production systems.
- Evaluate AI behavior rigorously and establish measurable performance frameworks.
- Partner with product and engineering teams to determine when AI is appropriate.
- Turn experiments into useful, reliable, measurable, safe, and cost-aware production features.
- Build evaluation discipline into the delivery process.
- Help client teams make informed decisions about where AI creates real value.
Requirements:
- 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: Experience with Claude, GPT, Azure OpenAI, open-source models, model routing, fine-tuning, distillation, or small/edge models.
- Desired: Experience with MCP, A2A, multi-agent orchestration, AI tool calling, or agent evaluation.
- Desired: Experience with LLM-as-judge approaches calibrated against human evaluation.
- Desired: Experience with semantic knowledge management, ontologies, knowledge graphs, or semantic layers.
- Desired: Experience with AI development lifecycle practices across data, build, evaluation, deployment, monitoring, and continuous improvement.
- Desired: Experience using AI-assisted development tools while maintaining strong review, testing, and safety discipline.
Benefits:
- paid vacation
- vacation premium
- Aguinaldo
- pantry vouchers
- internet and home office allowances
- major medical and life insurance
- employee referral bonus program
- annual training and professional development allowance
- full-time employment stability
- opportunities for continuous learning and career growth
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