Staff AI Engineer

Staff AI Engineer
Ready to be a Titan?
In this senior and highly influential position, you will drive the development of our cutting-edge AI Voice Agents and conversational systems. You will act as the primary technical leader for the product, navigating ambiguity and delivering robust, scalable solutions that redefine customer experiences. You will engage with leadership across engineering, infrastructure, data science, and product growth. We build for perfection, use Python and the most modern tools on Azure Cloud, have an amazing culture, and love to solve complex, real-time problems.

What you'll do:

• Contribute significantly to the technical roadmap for the AI Voice Agent system and ensure execution aligns with product and business goals.

• Serve as the technical lead and subject matter expert for critical projects, actively mentoring and guiding engineers on best practices in AIOps, LLMOps, system design, and implementation excellence.

• Collaborate with product teams to integrate and operationalize Foundational Models (like LLMs) and specialized speech models into production, focusing on high-volume, low-latency API usage, cost-efficiency, and resilience.

• Drive execution for complex, cross-functional projects, proactively identifying and resolving technical blockers in infrastructure, deployment, and real-time performance optimization.

• Communicate effectively with executives, product managers, customers, and partners, translating complex technical challenges into clear implementation plans and strategic recommendations.

What you'll bring:

• 8+ years of experience writing production-level code in Python.

• 3+ years of experience designing, deploying, and maintaining high-volume, low-latency production AI/ML systems, specifically Conversational AI models, ASR/TTS engines, or real-time NLP systems.

• Deep expertise in designing and deploying large-scale, fault-tolerant AI inference services and distributed systems to support real-time voice agents.

• Strong understanding of the Conversational AI and Machine Learning project lifecycle.

• Advanced knowledge of Machine Learning methods and algorithms across traditional ML methods and Deep Learning theory and techniques.

• Expertise in leveraging and orchestrating Foundational Models using tools like LangChain, LangGraph, or equivalent frameworks, including state-of-the-art prompting, agent design, and RAG (Retrieval-Augmented Generation) techniques.

• Experience with Reinforcement Learning (RL) techniques and implementing Continuous Learning/Online Optimization systems for production.

• Experience with deep learning frameworks (PyTorch, TensorFlow) and NLP/Speech-focused libraries (e.g., Hugging Face Transformers, DeepSpeech, Kaldi/ESPnet).

• Expert-level knowledge of data storage and analytics technologies (SQL Server, PostGreSQL, Redshift, Snowflake).

• Extensive experience with public cloud environments such as Azure or AWS, including security, cost management, and cloud-native architecture.

• Proven ability to architect solutions using microservices and asynchronous messaging technologies like Kafka, Azure ServiceBus, etc. (critical for high-volume, real-time interactions).

• Experience with serverless architecture (Azure Functions, AWS Lambda, etc.).

• Experience with Azure Cognitive Services (Speech/Bot Service) or similar cloud-based AI offerings is a significant plus.

• Expert command of Git, unit testing, debugging, profiling, and modern SDLC tools.

• Demonstrated ability to provide technical leadership and operate effectively in a fast-paced environment with a globally distributed team.

Be Human With Us:

Being human isn’t about checking every box on a list. It’s about the experiences we have, people we meet, and the perspectives we share. So, if you have the skills but are hesitant to apply because of your background, apply anyway. We need amazing people like you to help us challenge the conventional and think differently about the problems that we’re