We're looking for an
AI Engineer to join our AI and Data team, where you'll build and ship AI-powered products that directly improve customer service operations - from support chatbots and voice assistants to automated call analysis pipelines.
Your Future Tasks
- Design, develop, and maintain AI-powered chatbots for customer support, handling real customer queries at scale
- Build and improve voice processing pipelines — automatic speech recognition (ASR), text-to-speech (TTS)
- Develop agent-based systems using frameworks like Pydantic-AI or LangChain to automate customer service workflows
- Integrate LLMs into production services for tasks such as script compliance checking, call summarization, and intent classification
- Build and operate microservices that communicate via Kafka, expose REST APIs, and store artifacts in S3
- Experiment with prompt engineering approaches, evaluate model outputs against labeled data, and iterate on accuracy metrics
- Collaborate with the customer service and collections teams to understand business processes and translate them into AI solutions
- Own your products end-to-end — from research and prototyping through deployment, monitoring, and measuring economic impact
What We Expect
- Strong Python skills — this is our primary language for AI/ML services
- Basic understanding of machine learning concepts and hands-on experience with ML frameworks
- Experience with NLP: text classification, named entity recognition, semantic similarity, or related tasks
- Familiarity with LLM APIs (OpenAI, Anthropic, or similar) and prompt engineering techniques
- Experience building and deploying backend services (REST APIs, async processing, message queues)
- Comfort working with AWS services (S3, SageMaker, RDS, EKS)
- Understanding of CI/CD practices and containerized deployments
- Ability to work independently, move fast, and ship iteratively — our team values startup speed and MVP-first thinking
Nice to Have
- Experience with agent frameworks such as Pydantic-AI, LangChain, or similar orchestration tools
- Hands-on experience with ASR, TTS, or other voice/speech technologies
- Experience with GitOps workflows (Terraform, Flux) for infrastructure management
- Background in building customer-facing chatbots or voice assistants
- Familiarity with Kafka-based event-driven architectures
- Experience with multilingual NLP
- Knowledge of monitoring and observability tools (Grafana, Splunk)
