AI Engineer II & Senior AI Engineer - Getting Customers Ready for AI
Core
Design, build, and improve AI-powered solutions (ML models, LLM apps, RAG, agentic workflows) and scalable data pipelines to enable automation and decision-making for customers.
Role type
Senior IC AI Engineer (MLOps & AI Infrastructure)
Builds
AI-powered applications, services, APIs, and platforms integrating ML models and data pipelines.
Domain
Artificial Intelligence / Machine Learning / Data Engineering
Deliverable
production ML models | product features | infrastructure
Required skills
Python, C/C++/C#/Java/JavaScript, Machine Learning fundamentals, Statistics, Data processing, Distributed systems, Cloud-based AI/ML workloads, MLOps (CI/CD, model deployment, monitoring, versioning, containerization), LLMs, Vector databases, Retrieval systems, RAG architectures, Agentic workflows, Data pipeline development, System integration, Automation, Telemetry, Responsible AI practices.
Preferred skills
Rapid prototyping, Experimentation, Navigating ambiguity, Engineering excellence, Documentation, Governance, Security compliance.
Technologies
Python, C, C++, C#, Java, JavaScript, LLMs, Vector databases, Retrieval systems, RAG, MLOps tools, Cloud platforms.
Responsibilities
Design and build AI-powered solutions including ML models, LLM applications, RAG systems, and agentic workflows. Develop and operate scalable data pipelines, ETL processes, and training datasets. Deploy, monitor, and optimize AI systems using MLOps practices. Transform large-scale data into contextual intelligence and decision-support capabilities. Build and integrate AI capabilities into applications, services, APIs, and platforms. Contribute to AI readiness initiatives through frameworks, metrics, and solutions for customer adoption. Write maintainable, well-tested code and adhere to security, compliance, and Responsible AI practices.
Seniority
Senior, hands-on IC