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)

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