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 L7 · Distinguished AI Platform Engineer
Apply ai platform & mlops engineering capability at operates as a rare distinguished authority with enterprise or industry influence.
Las cinco dimensiones que cambian
- Autonomía
- Industry/frontier authority
- Alcance
- Operates as a rare distinguished authority with enterprise or industry influence.
- Complejidad
- Frontier
- Influencia
- Enterprise / industry
- Impacto en el negocio
- Enterprise / industry
- Ambigüedad
- High
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 L7.
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 L7 scope.
Habilidades esperadas en L7
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.
Humanas10
| Humanas | P | De apoyo |
|---|---|---|
| Clear verbal communicationCommunication & Language | P7Enterprise / Industry AuthorityDe apoyo | Acts as an industry-level authority in Clear verbal communication and creates new practices or standards. |
| Clear written communicationCommunication & Language | P7Enterprise / Industry AuthorityDe apoyo | Acts as an industry-level authority in Clear written communication and creates new practices or standards. |
| CollaborationCollaboration & Relationships | P7Enterprise / Industry AuthorityDe apoyo | Acts as an industry-level authority in Collaboration and creates new practices or standards. |
| Critical thinkingThinking & Problem Solving | P7Enterprise / Industry AuthorityDe apoyo | Acts as an industry-level authority in Critical thinking and creates new practices or standards. |
| Cross-functional collaborationCollaboration & Relationships | P7Enterprise / Industry AuthorityDe apoyo | Acts as an industry-level authority in Cross-functional collaboration and creates new practices or standards. |
| Learning agilityExecution & Self-Management | P7Enterprise / Industry AuthorityDe apoyo | Acts as an industry-level authority in Learning agility and creates new practices or standards. |
| MentoringCollaboration & Relationships | P7Enterprise / Industry AuthorityDe apoyo | Acts as an industry-level authority in Mentoring and creates new practices or standards. |
| Stakeholder alignmentInfluence & Leadership Without Authority | P7Enterprise / Industry AuthorityDe apoyo | Acts as an industry-level authority in Stakeholder alignment and creates new practices or standards. |
| Strategic thinkingThinking & Problem Solving | P7Enterprise / Industry AuthorityDe apoyo | Acts as an industry-level authority in Strategic thinking and creates new practices or standards. |
| Structured problem solvingThinking & Problem Solving | P7Enterprise / Industry AuthorityDe apoyo | Acts as an industry-level authority in Structured problem solving and creates new practices or standards. |
Profesionales6
| Profesionales | P | De apoyo |
|---|---|---|
| AI lifecycle governanceData & Analytics Practice | P7Enterprise / Industry AuthorityCentral | Acts as an industry-level authority in AI lifecycle governance and creates new practices or standards. |
| AI model governanceData & Analytics Practice | P7Enterprise / Industry AuthorityCentral | Acts as an industry-level authority in AI model governance and creates new practices or standards. |
| Architecture governanceIT Service Management & Governance | P7Enterprise / Industry AuthorityDe apoyo | Acts as an industry-level authority in Architecture governance and creates new practices or standards. |
| Model risk managementData & Analytics Practice | P7Enterprise / Industry AuthorityCentral | Acts as an industry-level authority in Model risk management and creates new practices or standards. |
| Responsible AI principlesData & Analytics Practice | P7Enterprise / Industry AuthorityDe apoyo | Acts as an industry-level authority in Responsible AI principles and creates new practices or standards. |
| Technology governanceIT Service Management & Governance | P7Enterprise / Industry AuthorityDe apoyo | Acts as an industry-level authority in Technology governance and creates new practices or standards. |
Técnicas16
| Técnicas | P | De apoyo |
|---|---|---|
| AI inference optimizationData Science, ML & AI | P7Enterprise / Industry AuthorityDe apoyo | Advances the state of practice for AI inference optimization and influences the profession beyond the organization. |
| AI observabilityData Science, ML & AI | P7Enterprise / Industry AuthorityCentral | Advances the state of practice for AI observability and influences the profession beyond the organization. |
| Apache SparkDatabases & Data Platforms | P7Enterprise / Industry AuthorityDe apoyo | Advances the state of practice for Apache Spark and influences the profession beyond the organization. |
| DatabricksDatabases & Data Platforms | P7Enterprise / Industry AuthorityDe apoyo | Advances the state of practice for Databricks and influences the profession beyond the organization. |
| Feature pipeline engineeringData Science, ML & AI | P7Enterprise / Industry AuthorityDe apoyo | Advances the state of practice for Feature pipeline engineering and influences the profession beyond the organization. |
| Feature store engineeringData Science, ML & AI | P7Enterprise / Industry AuthorityDe apoyo | Advances the state of practice for Feature store engineering and influences the profession beyond the organization. |
| KubernetesDevOps, SRE & Platform Engineering | P7Enterprise / Industry AuthorityDe apoyo | Advances the state of practice for Kubernetes and influences the profession beyond the organization. |
| ML experiment trackingData Science, ML & AI | P7Enterprise / Industry AuthorityCentral | Advances the state of practice for ML experiment tracking and influences the profession beyond the organization. |
| MLOpsData Science, ML & AI | P7Enterprise / Industry AuthorityCentral | Advances the state of practice for MLOps and influences the profession beyond the organization. |
| MLflowData Science, ML & AI | P7Enterprise / Industry AuthorityCentral | Advances the state of practice for MLflow and influences the profession beyond the organization. |
| Model deploymentData Science, ML & AI | P7Enterprise / Industry AuthorityCentral | Advances the state of practice for Model deployment and influences the profession beyond the organization. |
| Model drift detectionData Science, ML & AI | P7Enterprise / Industry AuthorityDe apoyo | Advances the state of practice for Model drift detection and influences the profession beyond the organization. |
| Model monitoringData Science, ML & AI | P7Enterprise / Industry AuthorityCentral | Advances the state of practice for Model monitoring and influences the profession beyond the organization. |
| Model registryData Science, ML & AI | P7Enterprise / Industry AuthorityCentral | Advances the state of practice for Model registry and influences the profession beyond the organization. |
| Model servingData Science, ML & AI | P7Enterprise / Industry AuthorityCentral | Advances the state of practice for Model serving and influences the profession beyond the organization. |
| TerraformDevOps, SRE & Platform Engineering | P7Enterprise / Industry AuthorityDe apoyo | Advances the state of practice for Terraform and influences the profession beyond the organization. |
Es el nivel más alto de esta carrera.
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.