Senior AI/AIOps Engineer

Oracle; México; Presencial; MXN 1,282,000 - 1,832,000; Jornada completa

Descripción de la vacante

A leading technology firm located in Mexico is seeking an experienced professional to design and implement large-scale data pipelines using cloud services. The role requires strong proficiency in programming languages such as Python and Java, and a solid understanding of distributed systems. Candidates should have a bachelor's or master's in a relevant field and at least 5 years of experience in building data platforms. This position includes mentoring junior engineers and involves collaboration with cross-functional teams.

Formación

• 5+ years building distributed systems or production-grade data platforms in cloud.
• Experience with cloud-native architectures — especially OCI, AWS, Azure, or GCP.
• Production experience with big data compute engines: Spark, Flink, or Trino.

Responsabilidades

• Design and implement large-scale, fault-tolerant data pipelines on OCI.
• Build and manage streaming data architectures using tools like OCI GoldenGate.
• Serve as a technical leader, mentoring junior engineers.

Conocimientos

Python

Java

Scala

SQL

PLSQL

Kafka

Flink

Educación

Bachelor's or Master's degree in Computer Science, Engineering

Herramientas

OCI Data Integration

OCI Data Flow

OCI Streaming

Terraform

Docker

Kubernetes

Descripción del empleo

What You’ll Be Doing (Core Mission)

• Design and implement large-scale, fault-tolerant data pipelines on OCI, using services like OCI Data Integration, OCI Data Flow (Apache Spark), Object Storage, and Autonomous Database.
• Build and manage streaming data architectures menggunakan alat seperti OCI GoldenGate, Apache Kafka, dan Spark/Flink Streaming.
• Enforce standards dan automation across the entire data lifecycle, including schema evolution, dataset migration, and deprecation strategies.
• Improve platform resilience, data quality, and observability dengan advanced monitoring, alerting, dan automated data governance.
• Serve as a technical leader, mentoring junior engineers, reviewing designs and code, dan promoting engineering best practices.
• Collaborate cross-functionally dengan ML engineers, platform teams, and data scientists to integrate data services with AI/ML workloads.
• Partner in AI pipeline enablement, ensuring Lakehouse services efficiently support model training, feature engineering, and real-time inference.

Required Technical Skills & Experience

Engineering & Infrastructure

• 5+ years building distributed systems or production-grade data platforms di cloud.
• Strong coding proficiency in Python, Java, atau Scala, with an emphasis on performance and reliability.
• Expertise in SQL and PLSQL, data modeling, and query optimization.
• Proven experience with cloud-native architectures—especially OCI, AWS, Azure, or GCP.

Lakehouse & Streaming Mastery

• Deep knowledge of modern lakehouse/table formats: Apache Iceberg, Delta Lake, atau Apache Hudi.
• Production experience with big data compute engines: Spark, Flink, or Trino.
• Skilled in real-time streaming and event-driven architectures using Kafka, Flink, GoldenGate, or Streaming.
• Experience managing data lakes, catalogs, and metadata governance in large-scale environments.

AI/ML Integration

• Hands-on experience enabling ML pipelines: from data ingestion to model training and deployment.
• Familiarity with ML frameworks (e.g., PyTorch, XGBoost, scikit-learn).
• Understanding of modern ML architectures: termasuk RAG, prompt chaining, and agent-based workflows.
• Awareness of MLOps practices, including model versioning, feature stores, and integration with AI pipelines.

DevOps & Operational Excellence

• Deep understanding of CI/CD, infrastructure-as-code (IaC), and release automation using tools like Terraform, GitHub Actions, atau CloudFormation.
• Experience with Docker, Kubernetes, dan cloud-native container orchestration.
• Strong focus on testing, documentation, and system observability (Prometheus, Grafana, ELK stack).
• Comfortable dengan cost/performance tuning, incident response, dan data security standards (IAM, encryption, auditing).

Preferred Qualifications

• Experience with Oracle’s cloud-native tools: OCI Data Integration, Data Flow, Autonomous Database, GoldenGate, OCI Streaming.
• Experience with query engines seperti Trino atau Presto, dan tools seperti db atau Apache Air流 .
• Familiarity dengan data cataloging, RBAC/ABAC, dan enterprise data governance frameworks。
• Exposure to vector数据库 dan LLM tooling (embeddings, vector search, prompt orchestration).
• Solid understanding of data warehouse design principles, star/snowflake schemas, and ETL optimization.

Minimum Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related technical field.
• 4–6 year’s experience designing and building cloud-based data pipelines and distributed systems.
• Proficiency dalam setidaknya satu bahasa inti: Python, Java, atau Scala.
• Familiar with lakehouse formats (Iceberg, Delta, Hudi), file formats (Parquet, ORC, Avro), and streaming platforms (Kafka, Kinesis).
• Strong understanding of distributed systems fundamentals: partitioning, replication, idempotency, consensus protocols.

Soft Skills & Team Expectations

• Proven ability to lead technical initiatives independently, end-to-end.
• Comfortable working in cross-functional teams and mentoring junior engineers.
• Excellent problem-solving skills, design thinking, and attention to operational excellence.
• Passion for learning emerging data and AI technologies and sharing knowledge across teams.

Career Level - IC4

Oracle is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law. Oracle will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.