Software Developer 4

hace 7 días

Ciudad de México, Ciudad de México Oracle A tiempo completo
Description

Education & Experience

  • BS in Computer Science or equivalent practical experience.
  • 6-9 years of experience building and operating distributed systems.
  • Proven experience delivering cloud-native platforms used in production.

Core Technical Skills

  • Strong proficiency in Python and shell scripting.
  • Hands-on experience with Kubernetes and container orchestration.
  • Experience building distributed systems with high availability requirements.
  • Strong Linux, networking, and system troubleshooting skills.

AI Platform Knowledge

  • Experience supporting model training and serving pipelines.
  • Understanding of LLM, ASR, and TTS serving patterns.
  • Experience with prompt engineering and prompt lifecycle management.
  • Familiarity with vector databases and retrieval-based AI systems.
  • Ability to evaluate AI system performance from a platform perspective.

Preferred Qualifications

  • MS in Computer Science or related field.
  • Production experience on OCI, AWS, or Azure.
  • Experience with LLM serving frameworks (KServe, Triton, Kubeflow, etc.).
  • Experience with model optimization technologies (DeepSpeed, FasterTransformer).
  • Familiarity with deep learning frameworks (PyTorch, TensorFlow, JAX).
  • Experience building conversational voice AI systems (ASR, TTS, NLP).
  • Exposure to AIOps or AI-driven observability solutions.

IC4 Scope Clarification

  • Owns design and implementation of AI infrastructure systems.
  • Leads technical initiatives without people management responsibility.
  • Influences architecture within a defined platform area.
  • Bridges applied science and production engineering.
Responsibilities

AI Infrastructure & Automation

  • Design and build automation frameworks for AI model training, deployment, and lifecycle management.
  • Own and evolve model serving platforms to ensure high availability, scalability, and performance.
  • Develop tooling for zero-touch deployments, rollbacks, and upgrades of AI services.
  • Build self-service APIs and workflows for applied scientists and application teams.

AI Serving & Platform Engineering

  • Engineer high-performance model serving systems for LLMs, ASR, TTS, and conversational AI workloads.
  • Optimize inference latency, throughput, and resource utilization.
  • Partner with applied scientists to productionize models safely and efficiently.
  • Support multi-model and multi-tenant serving architectures.

Cloud-Native Software Development

  • Design and implement backend services in Python (primary), Java or Go.
  • Build REST and event-driven services that integrate AI platforms with contact center systems.
  • Write production-quality code with strong testing, observability, and CI/CD integration.

Reliability, Observability & Operations

  • Define and implement observability standards (metrics, logs, traces) for AI services.
  • Lead troubleshooting efforts for training and serving failures.
  • Drive incident postmortems and ensure durable, automated fixes.
  • Apply SLOs, SLIs, and error budgets to AI platforms.

Technical Leadership

  • Own end-to-end delivery of complex AI infrastructure initiatives.
  • Mentor IC3 engineers and influence best practices.
  • Review designs and code to ensure scalability, security, and maintainability.
  • Act as a technical escalation point within the AI infrastructure domain.
Qualifications

Career Level - IC4

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