AI Engineer – Conversational Systems (RASA, GCP)

About the role

We are looking for a motivated AI/ML Engineer (Level II) to design, develop and deploy advanced conversational AI solutions using the RASA framework on Google Cloud Platform. The role involves moving from prototype to production, owning components, and ensuring reliability of enterprise‑grade virtual assistants.

Key responsibilities

• Design, build and maintain sophisticated RASA agents, including dialogue management, NLU pipeline configuration and custom actions.
• Train, evaluate and fine‑tune NLU and dialogue models, applying continuous‑improvement loops based on analytics and user feedback.
• Develop clean, well‑documented Python code for backend services, APIs and integrations with business systems.
• Architect, deploy and manage RASA bots on GCP services such as GKE, Cloud Run, Pub/Sub, Vertex AI and Dialogflow CX, and integrate speech‑to‑text/text‑to‑speech capabilities.

Required profile

• Bachelor’s degree in Computer Science, Engineering, Data Science or equivalent practical experience.
• Minimum 3 years of professional AI/ML development experience, with at least 2 years building production‑level chat‑bots using RASA.
• Strong Python programming skills and solid software‑engineering practices.
• Hands‑on experience with core GCP services (GKE, Cloud Run, Cloud Storage, BigQuery, IAM, VPC, Vertex AI, Dialogflow, Speech‑to‑Text, Text‑to‑Speech).
• Proficiency with machine‑learning libraries such as scikit‑learn, spaCy and Transformers.
• Expertise in version control using Git and collaborative development in an Agile/Scrum environment.

Required skills

• Python
• RASA Framework (Open Source, X/Pro)
• Google Cloud Platform – GKE, Cloud Run, Compute Engine, Pub/Sub, Cloud Storage, BigQuery, Vertex AI, Dialogflow, Speech‑to‑Text, Text‑to‑Speech
• scikit‑learn, spaCy, Transformers
• Git
• Docker, Kubernetes
• Terraform (infrastructure‑as‑code)