Sr. AI Engineer

We are seeking a Senior AI Engineer to join a growing AI team focused on contact center–driven solutions, including Agent Assist, virtual agents, and AI-powered internal tooling. This role will play a critical part in delivering end-to-end AI solutions—from ideation and proof of concept through MVP deployment and production support.

The ideal candidate is a hands‑on engineer with deep Python expertise, strong experience building backend systems and APIs, and practical exposure to LLMs, NLP, and agentic AI workflows. This role partners closely with data scientists but is engineering‑led, with ownership of implementation, scalability, and integration into real‑world applications.

• Design, build, and deploy AI‑driven applications leveraging LLMs, NLP, and modern AI frameworks
• Real‑time or post‑call summarization
• Implement and maintain LLM‑powered services, including experimentation with RAG‑based architectures and internal models
• Collaborate with data scientists developing in‑house models and translate research into production‑ready systems
• Build and maintain scalable backend services using Python (e.g., FastAPI), supporting AI workflows and integrations
• Work with cloud‑native services (AWS preferred) to deploy, scale, and secure AI applications

• Web extensions and lightweight front‑end applications
• AI services integrated into contact center platforms
• Infrastructure, Dev Ops & Delivery
• Own projects end‑to‑end, from initial design through production deployment
• Contribute to CI/CD pipelines using Git Hub, Git Lab, or Jenkins
• Work with infrastructure‑as‑code tools (e.g., Terraform) to support scalable, repeatable deployments
• Monitor, maintain, and enhance production AI systems
• Work effectively in a small, evolving, and loosely structured team
• Partner with product, business stakeholders, and other engineers to align AI solutions with business outcomes
• Apply an experimental mindset, researching new approaches and building POCs to validate concepts quickly
• Communicate architecture decisions, tradeoffs, and system behavior clearly to technical and non‑technical audiences

• Building production‑grade backend systems (not notebook‑only work)
• API development (FastAPI or equivalent)
• Concurrency / multithreading and performance optimization
• Strong hands‑on experience with:
• NLP and Large Language Models (LLMs)
• Modern AI/ML tooling and frameworks
• Cloud experience with AWS preferred (GCP, Azure acceptable)
• CI/CD experience using Git Hub, Git Lab, Jenkins, or similar tools
• Professional Skills
• Proven ability to operate independently and in ambiguous environments
• Strong collaboration and communication skills
• Passion for staying current with AI trends, tools, and techniques
• Comfortable working across engineering and data science boundaries

• Experience building Retrieval‑Augmented Generation (RAG) solutions
• Exposure to agentic AI workflows or autonomous LLM‑based systems
• Experience translating data science models into production systems

• PyTorch, Scikit‑learn
• Financial services or banking domain experience

• Delivering a working Agent Assist MVP into a live or pilot environment
• Establishing patterns for LLM usage, API design, and deployment across the AI team
• Helping shape the future architecture and direction of AI capabilities within the contact center ecosystem