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 L5 · Senior Staff AI Platform Engineer
Apply ai platform & mlops engineering capability at shapes standards, architecture or operating practice across a broad domain.
Las cinco dimensiones que cambian
- Autonomía
- Domain-wide authority
- Alcance
- Shapes standards, architecture or operating practice across a broad domain.
- Complejidad
- Systemic
- 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 L5.
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 L5 scope.
Habilidades esperadas en L5
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 | P5AdvancedDe apoyo | Defines advanced approaches for Clear verbal communication and shapes standards across a domain. |
| Clear written communicationCommunication & Language | P5AdvancedDe apoyo | Defines advanced approaches for Clear written communication and shapes standards across a domain. |
| CollaborationCollaboration & Relationships | P5AdvancedDe apoyo | Defines advanced approaches for Collaboration and shapes standards across a domain. |
| Critical thinkingThinking & Problem Solving | P5AdvancedDe apoyo | Defines advanced approaches for Critical thinking and shapes standards across a domain. |
| Cross-functional collaborationCollaboration & Relationships | P5AdvancedDe apoyo | Defines advanced approaches for Cross-functional collaboration and shapes standards across a domain. |
| Learning agilityExecution & Self-Management | P5AdvancedDe apoyo | Defines advanced approaches for Learning agility and shapes standards across a domain. |
| MentoringCollaboration & Relationships | P5AdvancedDe apoyo | Defines advanced approaches for Mentoring and shapes standards across a domain. |
| Stakeholder alignmentInfluence & Leadership Without Authority | P5AdvancedDe apoyo | Defines advanced approaches for Stakeholder alignment and shapes standards across a domain. |
| Strategic thinkingThinking & Problem Solving | P5AdvancedDe apoyo | Defines advanced approaches for Strategic thinking and shapes standards across a domain. |
| Structured problem solvingThinking & Problem Solving | P5AdvancedDe apoyo | Defines advanced approaches for Structured problem solving and shapes standards across a domain. |
Profesionales6
| Profesionales | P | De apoyo |
|---|---|---|
| AI lifecycle governanceData & Analytics Practice | P5AdvancedCentral | Defines advanced approaches for AI lifecycle governance and shapes standards across a domain. |
| AI model governanceData & Analytics Practice | P5AdvancedCentral | Defines advanced approaches for AI model governance and shapes standards across a domain. |
| Architecture governanceIT Service Management & Governance | P5AdvancedDe apoyo | Defines advanced approaches for Architecture governance and shapes standards across a domain. |
| Model risk managementData & Analytics Practice | P5AdvancedCentral | Defines advanced approaches for Model risk management and shapes standards across a domain. |
| Responsible AI principlesData & Analytics Practice | P5AdvancedDe apoyo | Defines advanced approaches for Responsible AI principles and shapes standards across a domain. |
| Technology governanceIT Service Management & Governance | P5AdvancedDe apoyo | Defines advanced approaches for Technology governance and shapes standards across a domain. |
Técnicas16
| Técnicas | P | De apoyo |
|---|---|---|
| AI inference optimizationData Science, ML & AI | P5AdvancedDe apoyo | Designs advanced approaches using AI inference optimization and establishes reusable patterns across teams. |
| AI observabilityData Science, ML & AI | P5AdvancedCentral | Designs advanced approaches using AI observability and establishes reusable patterns across teams. |
| Apache SparkDatabases & Data Platforms | P5AdvancedDe apoyo | Designs advanced approaches using Apache Spark and establishes reusable patterns across teams. |
| DatabricksDatabases & Data Platforms | P5AdvancedDe apoyo | Designs advanced approaches using Databricks and establishes reusable patterns across teams. |
| Feature pipeline engineeringData Science, ML & AI | P5AdvancedDe apoyo | Designs advanced approaches using Feature pipeline engineering and establishes reusable patterns across teams. |
| Feature store engineeringData Science, ML & AI | P5AdvancedDe apoyo | Designs advanced approaches using Feature store engineering and establishes reusable patterns across teams. |
| KubernetesDevOps, SRE & Platform Engineering | P5AdvancedDe apoyo | Designs advanced approaches using Kubernetes and establishes reusable patterns across teams. |
| ML experiment trackingData Science, ML & AI | P5AdvancedCentral | Designs advanced approaches using ML experiment tracking and establishes reusable patterns across teams. |
| MLOpsData Science, ML & AI | P5AdvancedCentral | Designs advanced approaches using MLOps and establishes reusable patterns across teams. |
| MLflowData Science, ML & AI | P5AdvancedCentral | Designs advanced approaches using MLflow and establishes reusable patterns across teams. |
| Model deploymentData Science, ML & AI | P5AdvancedCentral | Designs advanced approaches using Model deployment and establishes reusable patterns across teams. |
| Model drift detectionData Science, ML & AI | P5AdvancedDe apoyo | Designs advanced approaches using Model drift detection and establishes reusable patterns across teams. |
| Model monitoringData Science, ML & AI | P5AdvancedCentral | Designs advanced approaches using Model monitoring and establishes reusable patterns across teams. |
| Model registryData Science, ML & AI | P5AdvancedCentral | Designs advanced approaches using Model registry and establishes reusable patterns across teams. |
| Model servingData Science, ML & AI | P5AdvancedCentral | Designs advanced approaches using Model serving and establishes reusable patterns across teams. |
| TerraformDevOps, SRE & Platform Engineering | P5AdvancedDe apoyo | Designs advanced approaches using Terraform and establishes reusable patterns across teams. |
Qué cambia al pasar de L5 a L6
Moving from Senior Staff AI Platform Engineer to Principal 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 L6-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.