AI Platform & MLOps Engineering
AI Platform & MLOps Engineering is an individual-contributor Data + AI career progressing from guided delivery to enterprise expertise without requiring people management.
- Función
- Data & Analytics
- Arquetipo
- Engineering
- Nivel más alto
- L7 · Distinguished AI Platform Engineer
Para qué existe
Builds and operates platforms, deployment systems, evaluations, observability and controls required to run ML and AI reliably at production scale.
Responsabilidades típicas
Deliver ai platform & mlops engineering outcomes; apply data/AI standards; manage quality, reliability and risk; collaborate across product, engineering, security, legal and business teams; at senior levels shape enterprise standards and strategy.
Dónde se trabaja
Technology companies, data/cloud platforms, financial services, consulting, shared services, product engineering and regulated enterprises adopting Data + AI.
Cómo avanza la carrera
Associate AI Platform Engineer → AI Platform Engineer → Senior AI Platform Engineer → Staff AI Platform Engineer → Senior Staff AI Platform Engineer → Principal AI Platform Engineer → Distinguished AI Platform Engineer
Niveles de esta carrera
Seis etapas estándar. La séptima existe solo donde la carrera la contempla.
- L1Associate AI Platform Engineer
- L2AI Platform Engineer
- L3Senior AI Platform Engineer
- L4Staff AI Platform Engineer
- L5Senior Staff AI Platform Engineer
- L6Principal AI Platform Engineer
- L7Distinguished AI Platform Engineer
Nivel distinguido opcional. No todas las carreras llegan acá.
Qué se espera en L1 · Associate AI Platform Engineer
Apply ai platform & mlops engineering capability at learns the discipline and executes defined work with guidance.
Las cinco dimensiones que cambian
- Autonomía
- Close guidance
- Alcance
- Learns the discipline and executes defined work with guidance.
- Complejidad
- Defined
- Influencia
- Immediate team
- Impacto en el negocio
- Task/team
- Ambigüedad
- Low
Cómo se ve un buen desempeño
Produces trustworthy ai platform & mlops engineering outcomes, makes sound trade-offs, communicates evidence and risks, and demonstrates the autonomy and impact expected at L1.
Evidencia típica
Completed ai platform & mlops engineering work products or production outcomes; documented decisions; measurable improvements in quality, reliability, risk, speed, cost or business outcomes; peer/stakeholder evidence of L1 scope.
Habilidades esperadas en L1
Agrupadas en humanas, profesionales y técnicas. La proficiencia meta usa la escala P1–P7, y cada fila dice qué significa ese nivel para esa habilidad.
Humanas6
| Humanas | P | De apoyo |
|---|---|---|
| Clear verbal communicationCommunication & Language | P1AwarenessDe apoyo | Understands the purpose, vocabulary and basic principles of Clear verbal communication; works with close guidance. |
| Clear written communicationCommunication & Language | P1AwarenessDe apoyo | Understands the purpose, vocabulary and basic principles of Clear written communication; works with close guidance. |
| CollaborationCollaboration & Relationships | P1AwarenessDe apoyo | Understands the purpose, vocabulary and basic principles of Collaboration; works with close guidance. |
| Critical thinkingThinking & Problem Solving | P1AwarenessDe apoyo | Understands the purpose, vocabulary and basic principles of Critical thinking; works with close guidance. |
| Cross-functional collaborationCollaboration & Relationships | P1AwarenessDe apoyo | Understands the purpose, vocabulary and basic principles of Cross-functional collaboration; works with close guidance. |
| Structured problem solvingThinking & Problem Solving | P1AwarenessDe apoyo | Understands the purpose, vocabulary and basic principles of Structured problem solving; works with close guidance. |
Profesionales6
| Profesionales | P | De apoyo |
|---|---|---|
| AI lifecycle governanceData & Analytics Practice | P1AwarenessCentral | Understands the purpose, vocabulary and basic principles of AI lifecycle governance; works with close guidance. |
| AI model governanceData & Analytics Practice | P1AwarenessCentral | Understands the purpose, vocabulary and basic principles of AI model governance; works with close guidance. |
| Architecture governanceIT Service Management & Governance | P1AwarenessDe apoyo | Understands the purpose, vocabulary and basic principles of Architecture governance; works with close guidance. |
| Model risk managementData & Analytics Practice | P1AwarenessCentral | Understands the purpose, vocabulary and basic principles of Model risk management; works with close guidance. |
| Responsible AI principlesData & Analytics Practice | P1AwarenessDe apoyo | Understands the purpose, vocabulary and basic principles of Responsible AI principles; works with close guidance. |
| Technology governanceIT Service Management & Governance | P1AwarenessDe apoyo | Understands the purpose, vocabulary and basic principles of Technology governance; works with close guidance. |
Técnicas8
| Técnicas | P | De apoyo |
|---|---|---|
| AI observabilityData Science, ML & AI | P1AwarenessDe apoyo | Recognizes the purpose, core concepts and risks of AI observability; performs only guided exercises. |
| ML experiment trackingData Science, ML & AI | P1AwarenessDe apoyo | Recognizes the purpose, core concepts and risks of ML experiment tracking; performs only guided exercises. |
| MLOpsData Science, ML & AI | P1AwarenessCentral | Recognizes the purpose, core concepts and risks of MLOps; performs only guided exercises. |
| MLflowData Science, ML & AI | P1AwarenessCentral | Recognizes the purpose, core concepts and risks of MLflow; performs only guided exercises. |
| Model deploymentData Science, ML & AI | P1AwarenessCentral | Recognizes the purpose, core concepts and risks of Model deployment; performs only guided exercises. |
| Model monitoringData Science, ML & AI | P1AwarenessDe apoyo | Recognizes the purpose, core concepts and risks of Model monitoring; performs only guided exercises. |
| Model registryData Science, ML & AI | P1AwarenessDe apoyo | Recognizes the purpose, core concepts and risks of Model registry; performs only guided exercises. |
| Model servingData Science, ML & AI | P1AwarenessCentral | Recognizes the purpose, core concepts and risks of Model serving; performs only guided exercises. |
Qué cambia al pasar de L1 a L2
Moving from Associate AI Platform Engineer to AI Platform Engineer means greater autonomy, complexity, scope, influence and evidence of impact—not simply more tools.
Cómo se demuestra que ya estás
Sustained evidence of operating at L2-type scope: handles representative complexity, influences expected stakeholders and produces durable measurable outcomes.
Cómo prepararse
Take on one assignment at next-level scope; seek feedback; document decisions/outcomes; mentor others where appropriate; close highest-priority skill gaps.
Carreras cercanas
Calculadas por habilidades compartidas. Es una señal para explorar, no una garantía de contratación ni de elegibilidad.
- AI Governance & Responsible AIData & Analytics14 habilidades compartidas
- Data ArchitectureData & Analytics14 habilidades compartidas
- Analytics EngineeringData & Analytics12 habilidades compartidas
- Applied AI / Applied ScienceData & Analytics12 habilidades compartidas
- Data Governance & StewardshipData & Analytics9 habilidades compartidas
- Machine Learning EngineeringData & Analytics9 habilidades compartidas
Marco de carreras v21, activo desde 17 de agosto de 2026.