Applied AI Engineer

This is a fully remote position, open to applicants in Mexico.

📋 Description

• Develop and manage AI functionalities within an enterprise platform.

• Create agent runtimes, model routing, RAG, tool/function invocation, guardrails, evaluation, monitoring, cost oversight, latency enhancement, and production quality assurance.

• Deliver AI features that function reliably in production settings rather than merely in demonstrations.

• Transition AI systems from the prototyping phase to monitored production environments.

• Rigorously assess AI behavior.

• Collaborate with product and engineering teams to identify when AI is the appropriate solution.

• Convert experiments into production-ready features.

• Integrate evaluation discipline into the delivery pipeline.

• Assist client teams in making well-informed decisions regarding where AI can generate significant value.

⛳️ Requirements

• Proven experience in deploying software supported by LLMs, ML models, RAG systems, or agentic workflows to end-users in production.

• Background in designing or implementing agent runtime, orchestration, model routing, tool/function invocation, or AI workflow patterns.

• In-depth knowledge of RAG, grounding, retrieval quality, prompt design, context management, and evaluation methodologies.

• Experience in constructing evaluation frameworks, golden sets, regression tests, quality gates, or measurable AI performance metrics.

• Capability to regard cost, latency, reliability, and safety as paramount engineering constraints.

• Experience in establishing guardrails and controls for AI systems, including untrusted retrieved content, tool output risks, and failure modes.

• Proven track record in monitoring production AI behavior and enhancing systems based on data-driven insights.

• Solid software engineering expertise and the ability to work collaboratively with backend, platform, product, and security teams.

• Excellent communication and collaboration skills suited for client-facing consulting roles.

• Practical mindset with the ability to prioritize business value and deliver valuable AI functionalities swiftly and responsibly.

• Familiarity 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 invocation, or agent evaluation.

• Background in LLM-as-judge methodologies calibrated against human evaluation.

• Knowledge of semantic knowledge management, ontologies, knowledge graphs, or semantic layers.

• Familiarity with AI development lifecycle practices encompassing data, build, evaluation, deployment, monitoring, and continuous enhancement.

• Proficiency in utilizing AI-assisted development tools while upholding rigorous review, testing, and safety protocols.

🏝️ Benefits

• Flexible remote work arrangement.

• Permanent direct-hire employee position.

• Opportunity to collaborate with a global multi-billion dollar software corporation.

• Engaging client-facing consulting environment.