Software Developer 4

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