Saviynt is seeking a Principal Technical Support Engineer to drive the design, development, and deployment of AI-powered automation solutions that transform customer support operations. This role combines deep technical expertise in Artificial Intelligence and Machine Learning with strong program and stakeholder management capabilities.

What You'll Do

Design and implement AI/ML models for intelligent ticket routing, sentiment analysis, predictive support insights, and automated response generation.
Develop conversational AI solutions (chatbots and virtual assistants) using foundation models such as Claude, Titan, and Llama.
Build and manage Retrieval-Augmented Generation (RAG) knowledge systems with semantic search and intelligent recommendations.
Architect and implement agentic AI workflows for autonomous support automation.
Establish and mature MLOps practices including model versioning, monitoring and observability, retraining pipelines, and performance optimization.
Lead technical architecture decisions across AI infrastructure and cloud services.
Own end-to-end delivery of AI automation initiatives—from ideation through production deployment.
Define scope, timelines, milestones, and resource plans with clear accountability.
Lead agile ceremonies including sprint planning, daily stand-ups, retrospectives, and executive demos.
Proactively manage risks, dependencies, and technical blockers.
Coordinate cross-functional teams including data engineers, support operations, product managers, and leadership stakeholders.
Integrate AI solutions with existing support ecosystems (CRM, ticketing systems, knowledge bases).
Build scalable APIs and microservices for AI deployment and consumption.
Develop robust data pipelines for training data ingestion, preprocessing, and feature engineering.
Enforce engineering best practices including code quality standards, documentation, peer reviews, and testing frameworks.
Implement production-grade monitoring and observability for AI systems.
Partner with security and compliance teams to ensure responsible AI governance.
Identify high-impact AI leverage points across support operations and translate them into measurable automation initiatives.
Continuously evaluate emerging foundation models and AI tooling in the market; benchmark performance, cost, safety, and latency.
Architect scalable APIs and microservices for AI integration across CRM, ticketing, and knowledge platforms.
Partner with Product, Support Operations, Data Engineering, Security, and Leadership teams to deliver measurable business outcomes.

What We're Looking For

7+ years of software engineering experience, including 4+ years in AI/ML.
Strong hands-on experience with Python and modern ML frameworks (PyTorch, TensorFlow, Hugging Face or equivalent).
Proven experience building and deploying NLP/LLM-based systems in production.
Hands-on experience designing and implementing RAG architectures and working with vector databases.
Experience deploying ML systems in cloud environments.
Demonstrated ability to identify where AI can augment, automate, or eliminate operational workflows.
Experience building scalable APIs, microservices, and containerized applications (Docker, Kubernetes).
Strong understanding of MLOps, monitoring, and production observability.
Experience operating in enterprise environments with compliance considerations (SOC2, GDPR, etc.).
Strong executive communication skills and ownership mindset.