• Designing and enhancing AI-powered chatbots for customer interactions in billing, sales, and technical support to reduce reliance on human agents. • Automating business processes to improve operational efficiency using AI technologies. • Contributing to the development and maintenance of scalable AI infrastructures and integrate new machine learning techniques and large language models (LLMs) where applicable. • Evaluating and working with various AI models including LLMs, reasoning models, machine learning, and function calling models for different purposes. • Contributing to the roadmap for integrating speech-to-text functionality and real-time voice APIs, especially for telephony systems. • Working closely with other team members to evaluate and implement new AI technologies and tools, ensuring robust and reliable AI systems. • Participating in the testing and quality assurance of AI-driven systems, ensuring accurate and efficient performance. • Managing and maintaining AI agents across various platforms, ensuring their smooth operation and continuous improvement.

• Partner with DnA teammates, software engineers and business stakeholders to deliver high-impact, AI-enabled solutions • Integrate AI capabilities into internal tools, customer-facing products and operational workflows using APIs, cloud services and modern software development practices • Implement secure and compliant AI systems that align with company policies, regulatory expectations and responsible AI principles • Productionalize AI and machine learning solutions including generative AI, natural language processing, predictive modeling and automation workflows • Evaluate model performance, reliability, safety, bias, latency, cost and business impact; help establish monitoring and feedback loops for continuous improvement • Assist with the documentation of technical decisions, system architectures and model assumptions • Stay current on emerging AI tools, frameworks, model capabilities and industry best practices; recommend and implement pragmatic adoption strategies

• Work with team members on diverse projects and tasks. • Perform research and analysis to aid project objectives. • Create reports, presentations, and necessary documentation. • Engage in team meetings and share ideas. • Learn and implement industry best practices and company standards. • Support basic development and testing of AI chatbot features, including prompts, data inputs, and user interactions. • Help troubleshoot and improve chatbot performance by assisting with debugging, evaluations, and simple integrations. • Collect, clean, and preprocess large-scale manufacturing datasets. • Apply machine learning models (e.g., regression, classification, clustering) to identify trends, anomalies, and predictive insights. • Collaborate with engineers and operations teams to translate data findings into actionable recommendations. • Develop visualizations and dashboards to communicate results clearly to technical and non-technical stakeholders.

Role Description We're looking for a Full-Stack AI Engineer who builds production AI systems using Claude Code as a primary development tool. This role is for someone who combines strong full-stack engineering fundamentals with hands-on experience shipping AI-powered products, automations, and intelligent workflows into real environments. Claude Code is not optional here. You use it daily, you know how to get the most out of it, and it makes you meaningfully faster and better than engineers who do not. On top of that, you can design and build across the full stack, from backend services and APIs to frontend interfaces and AI integration layers, and you take ownership of systems end to end without needing close direction. If you build full-stack AI systems, ship automations that actually run in production, and use Claude Code as a core part of how you engineer, this role is built for you. Qualifications - 4+ years of professional software engineering experience with a strong full-stack background - Claude Code fluency: you use it daily in production and it is a core part of how you engineer - Demonstrated experience building and shipping full-stack AI systems in production including automations, AI agents, or LLM-integrated workflows - Strong system design fundamentals including APIs, databases, and distributed systems - Product-oriented mindset with strong ownership and the ability to execute without heavy oversight - Full availability during US business hours Requirements - Preferred but not strictly required: - Experience with TypeScript, Python, or similar backend technologies - Experience with modern frontend frameworks - Exposure to cloud infrastructure such as AWS or GCP - Experience with embeddings, vector databases, or retrieval systems Benefits - You will be paid in USD (bi-monthly: every 15th and 30th) - Paid Time Off in accordance with company policy - Observance of Holidays per company guidelines - 100% remote setup so you can work wherever you're most productive - High-ownership engineering role with direct impact on product and AI infrastructure - Opportunity to design and ship AI-powered systems from the ground up - Direct collaboration with product and engineering leadership How to Apply Please include: - Your updated resume - A short Loom video (1 to 2 minutes) walking through a full-stack AI system you built in production, how you used Claude Code throughout the development process, and what the system actually does Only candidates who submit a Loom video will be moved to the next step of the hiring process. Application Process Overview Our comprehensive selection process ensures we find the right fit for both you and our clients: - Initial Application - Submit your application and complete our prequalifying questions - Video Introduction - Record a video introduction to showcase your communication skills and work experience - Role-Specific Assessment - Complete a homework assignment tailored to the position (if applicable) - Recruitment Interview - Initial screening with our talent team - Executive Interview - Meet with senior leadership to discuss role alignment - Client Interview - Final interview with the client team you'd be supporting - Background & Reference Check - Professional reference verification - Job Offer - Successful candidates receive a formal offer to join the team Each stage is designed to evaluate your fit for the role while giving you insights into our company culture and expectations. We'll keep you informed throughout the process and provide feedback at each step.