Role overview
ClearlyRated is the leading CX platform designed specifically for B2B service firms. We offer firms a sophisticated alternative to manual processes and basic survey tools, then pair that with world class customer care and support. Ours is an efficient, industry-focused solution that provides data-driven insights to quip service teams with a real-time understanding of client and internal employee interactions and satisfaction. Our platform anticipates and resolves service issues before they impact customers, boosting satisfaction and unlocking new opportunities. In addition, our CRM & ATS integrations allow our clients to fully automate the process, providing a hands-off, always-on view of the health of their customer and employee relationships. And our industry-specific CX benchmarking and online reputation tools offer tangible proof of a firm's commitment to high-quality service, to differentiate from the competition and strengthen client trust.
What you'll work on
What You’ll Build**
Our AI roadmap is live and shipping. You’ll work on systems that go from training and evaluation to production monitoring:
– Survey timing optimization model — an ML system that learns the optimal moment to send a survey for each client relationship, maximizing response rates and data quality
– NLP pipeline for free-text feedback analysis — classifying, scoring, and extracting structured signals from open-ended survey responses across thousands of enterprise clients
– Client health scoring — an aggregate model that combines survey results, response patterns, historical sentiment, and relationship signals into a single predictive score per account
– Agentic AI architecture using LLM orchestration (Google Vertex AI / ADK) — multi-agent systems that reason over client data and surface proactive recommendations to account managers
– RAG system over enterprise knowledge bases — grounding LLM outputs in verified client data and platform knowledge
– MLOps infrastructure: model versioning, A/B testing, inference cost monitoring, drift detection, and production observability for agent loops
What we're looking for
– Experience with Google Cloud AI stack: Vertex AI, Google ADK, Pub/Sub for agent communication
– Multi-agent coordination patterns: orchestrator–worker, queue-based handoffs, tool use with guardrails
– Fine-tuning experience — LoRA, PEFT, or full fine-tuning on domain-specific data
– Java experience — our backend is Java/Spring Boot, and ML systems that integrate deeply with the platform need engineers who can cross that boundary
– MCP (Model Context Protocol) integration experience
– Experience with vector databases: Pinecone, Weaviate, pgvector