Lead Software Platform Engineer | AI Infrastructure & MLOps

Evolution USA is a high-growth technology company seeking a Lead Software Platform Engineer to manage the architecture and operational excellence of a cutting-edge AI and machine learning platform. This role involves defining deployment strategies for AI models and collaborating with various teams to ensure scalable and reliable systems that meet stringent compliance requirements.

Responsibilities:

• Owning the architecture and technical roadmap for a cloud-native AI and machine learning platform
• Designing and scaling infrastructure that supports model deployment, model lifecycle management, prompt management, and multi-model serving
• Building reliable systems for both real-time and batch inference workloads
• Developing frameworks for running and operating LLM-based applications, retrieval systems, and intelligent agent architectures in production
• Establishing platform-wide standards for security, governance, tenant isolation, and data protection
• Creating robust evaluation frameworks that measure model quality, detect regressions, and support safe releases
• Defining observability practices including monitoring, alerting, logging, tracing, and performance management
• Driving reproducibility, lineage, auditability, and compliance requirements across AI workflows
• Contributing to infrastructure automation and deployment processes using modern cloud engineering practices
• Leading technical design reviews and acting as a trusted advisor on architecture, scalability, reliability, and platform strategy
• Evaluating emerging AI technologies, frameworks, and tooling while making informed build-versus-buy decision
• Supporting operational excellence through incident response, production readiness reviews, and continuous improvement initiatives

Requirements:

• 10+ years of software engineering and cloud infrastructure experience
• Proven success designing and scaling distributed, cloud-native systems in production
• Experience serving as a technical lead, architect, or principal-level engineer responsible for major architectural decisions
• Deep hands-on experience building and operating AI/ML infrastructure at scale
• Strong knowledge of modern LLM architectures and production deployment patterns, including retrieval-augmented generation (RAG), prompt lifecycle management, embeddings, and tool integration
• Advanced coding skills in Python and TypeScript, with a strong focus on backend services and API development
• Experience with model lifecycle management, deployment workflows, and model-serving infrastructure
• Strong understanding of software quality, automated testing, release management, and CI/CD practices
• Familiarity with cloud-native technologies including AWS, containers, and infrastructure-as-code tooling
• Experience designing secure multi-tenant systems and handling sensitive or regulated data
• Expertise in monitoring, observability, reliability engineering, and service-level management
• Excellent communication skills with the ability to influence technical direction across multiple teams
• Production experience with agentic AI systems and orchestration frameworks
• Knowledge of advanced model serving, latency optimization, and cost management techniques
• Experience supporting multimodal AI workloads involving images or other complex data types
• Exposure to model optimization techniques such as fine-tuning, distillation, or performance tuning
• Background operating AI systems within regulated industries where auditability and compliance are critical
• Experience working in data-intensive, scientific, healthcare, pharmaceutical, or similarly complex environments