Loading...
LeadFull-timePythonRustAWSKubernetesDockerMicroservicesMachine LearningTensorFlowPyTorchGit
Salary Range
$153,000 - $207,000 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are looking for a Staff AI Engineer to join our Customer Support Automation team at Saviynt. This role will drive the design, development, and deployment of AI-powered automation solutions that transform customer support operations.
Key Responsibilities
- →Design and deploy production-grade AI/ML systems that automate and augment customer support workflows.
- →Build and scale LLM-powered solutions including RAG architectures, intelligent ticket routing, sentiment analysis, predictive insights, and automated response generation.
- →Develop conversational AI systems and agentic workflows for autonomous case handling.
- →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 to assess where we stand and recommend adoption when strategically justified.
- →Own the full lifecycle of AI initiatives from ideation through deployment, monitoring, and optimization.
- →Establish and mature MLOps practices including model versioning, observability, retraining pipelines, and cost-performance governance.
- →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.
- →Communicate technical architecture decisions and ROI clearly to executive stakeholders.
Requirements
- ✓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 (AWS experience, including Bedrock, is a strong advantage but not mandatory).
- ✓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.).
- ✓AI/ML certifications (AWS ML Specialty or equivalent) preferred.
- ✓Strong executive communication skills and ownership mindset.
Free to sign up. Takes 30 seconds.
