Job
Description
The Opportunity: We are seeking a talented and experienced Senior AI Engineer to play a pivotal role in developing and enhancing our conversational AI capabilities across multiple modalities (text, voice/telephony) and building intelligent agents to drive workflow automation. You will work closely with our Director of AI Engineering, product managers, and other engineering teams to bring our AI vision to life, primarily focusing on fine-tuning off-the-shelf Large Language Models (LLMs) and developing agentic systems for end-users (members, CBO staff, healthcare providers). This is a unique opportunity to apply your AI expertise to solve meaningful problems in the social and healthcare space, directly impacting people's lives. What You'll Do: Conversational AI Development & Fine-Tuning (Text & Voice): Lead the fine-tuning, evaluation, and deployment of pre-trained LLMs (e.g., Gemini, GPT series, open-source models) to create natural, empathetic, and effective conversational experiences for various user interactions via text-based channels (chat, SMS) and voice-based telephonic systems (IVR chatbots). Develop and implement strategies for data collection, preparation, and augmentation to support model fine-tuning and continuous improvement for both text and voice modalities. Design and implement robust evaluation frameworks to measure conversational AI performance, including metrics for accuracy, fluency, empathy, task completion, and call handling efficiency for telephonic agents. Work on prompt engineering, context management, and dialogue flow design to optimize conversational AI interactions across channels. Integrate and manage speech-to-text (STT) and text-to-speech (TTS) services for telephonic AI solutions. Agentic System Development: Design, build, and deploy AI agents that can reason, make decisions, and take actions to automate and optimize key workflows within the platform (e.g., intelligent referral initiation, proactive follow-ups, task management assistance). Develop agents capable of interacting with internal platform APIs, external data sources, and potentially third-party tools to achieve their goals. Explore and implement techniques for agent planning, tool usage, and multi-step reasoning. Collaboration & Technical Leadership: Collaborate closely with the Director of AI Engineering to define AI strategy, architecture, and technical roadmap for conversational AI and agentic systems. Partner with Product Managers to understand user needs and translate them into technical requirements for AI features. Work with platform and application engineers to integrate AI models and agents into the broader ecosystem. Mentor junior engineers and contribute to building a strong AI engineering culture. Stay up-to-date with the latest advancements in LLMs, conversational AI (text and voice), agent-based systems, and MLOps. MLOps & Productionization: Contribute to the development and maintenance of our MLOps infrastructure for training, deploying, monitoring, and iterating on AI models and agents in production. Ensure AI systems are scalable, reliable, and maintainable. Back-end Development: Solid understanding of back-end development principles and experience building or integrating with APIs (e.g., RESTful services) to connect AI models and agents with broader application systems. Familiarity with database technologies (SQL and/or NoSQL) and practical experience in how AI systems interact with data storage and retrieval for training, inference, and logging. What You'll Bring: Education: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Experience: 5+ years of hands-on experience in AI/ML engineering, with a significant focus on Natural Language Processing (NLP) and conversational AI. Demonstrable experience developing and deploying AI-powered telephonic chatbots or Interactive Voice Response (IVR) systems, including integration with STT/TTS technologies. Proven experience fine-tuning and deploying Large Language Models (LLMs) for specific tasks and domains. Strong understanding of model architectures, training techniques, and evaluation metrics. Demonstrable experience designing and building AI agents or systems that exhibit autonomous behavior, decision-making, and/or tool usage. Proficiency in Python and common AI/ML frameworks (e.g., TensorFlow, PyTorch, Hugging Face Transformers, LangChain, LlamaIndex). Experience with cloud platforms (GCP preferred, AWS/Azure acceptable) and their AI/ML services (e.g., Vertex AI, SageMaker, cloud telephony APIs). Solid understanding of MLOps principles and experience with tools for model deployment, monitoring, and CI/CD for ML. Skills: Strong analytical and problem-solving skills. Excellent communication and collaboration abilities. Ability to translate complex technical concepts to non-technical stakeholders. Proactive, self-starter with a passion for building impactful AI solutions. Nice to Haves: Experience working in the healthcare or social care domain. Familiarity with data privacy and security considerations in regulated environments (e.g., HIPAA). Experience with specific telephony platforms or APIs (e.g., Twilio, Vonage, Google Dialogflow CX). Contributions to open-source AI/ML projects.
