AI Engineer/Full Stack

• Build AI-powered solutions that address practical business challenges and improve productivity, decision-making, and user experiences.
• Develop applications that combine AI services, enterprise data, APIs, and modern user interfaces.
• Work across the full technology stack, including backend services, APIs, data integrations, AI/ML components, and frontend applications.
• Integrate LLMs and other AI capabilities into production applications, with appropriate consideration for security, reliability, scalability, and responsible AI practices.
• Develop solutions such as intelligent search and knowledge retrieval, automated summarization, recommendation capabilities, workflow automation, decision-support tools, and AI-assisted productivity applications.
• Collaborate with product managers, architects, data scientists, engineers, and business stakeholders to translate business requirements into technical solutions.
• Participate in architecture and technical design discussions and contribute to establishing engineering standards for a growing AI development organization.
• Build and deploy cloud-native applications using services and technologies across AWS, Azure, or Google Cloud.
• Implement modern DevOps and platform engineering practices, including containerization, Kubernetes, Infrastructure as Code, CI/CD, monitoring, and automated testing.
• Develop secure, reliable, maintainable, and highly available software suitable for enterprise environments.
• Take ownership of solutions from initial design and proof of concept through production deployment and continuous improvement.

Potential AI Initiatives

The team may work on a variety of AI-enabled capabilities, including:

• Intelligent meeting preparation and information gathering
• Automated conversation and call summarization
• Extraction of key insights, actions, and recommendations from unstructured information
• AI-powered knowledge search and retrieval
• Enterprise question-answering and knowledge assistants
• Intelligent recommendations and decision-support capabilities
• Automated task and workflow execution
• AI-enabled productivity tools
• Integration of enterprise data with LLM-based applications
• Solutions that connect AI capabilities with existing business applications, communication platforms, and data sources

• Bachelor’s degree in Computer Science, Engineering, or a related discipline, or equivalent practical experience.
• 8+ years of professional software engineering experience, with experience delivering production-quality applications.
• Strong experience designing and developing scalable applications, APIs, distributed systems, and enterprise software solutions.
• Hands-on experience working with Generative AI and Large Language Models (LLMs) and applying them to real-world business or technical problems.
• Strong full-stack development experience using technologies such as Python, TypeScript, Node.js, React, Next.js, and REST/API-based architectures.
• Experience developing backend services and integrating multiple data and enterprise systems.
• Experience deploying applications to at least one major cloud platform, such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
• Practical knowledge of Docker, Kubernetes, Infrastructure as Code, CI/CD, and cloud-native application development.
• Understanding of software architecture, object-oriented/design principles, distributed systems, application security, scalability, and reliability.
• Experience building solutions that can operate securely and reliably within large enterprise environments.
• Strong debugging, analytical, and problem-solving abilities.

Preferred Background

• Experience building RAG (Retrieval-Augmented Generation) or enterprise knowledge-retrieval solutions.
• Familiarity with vector databases, embeddings, prompt engineering, AI agents, or LLM orchestration frameworks.
• Experience integrating AI applications with enterprise APIs, databases, messaging systems, or other business platforms.
• Knowledge of observability, performance optimization, automated testing, and production monitoring.
• Experience working in Agile/Scrum or other collaborative software development environments.
• Ability to evaluate emerging AI technologies and determine where they can provide practical business value.

What We’re Looking For

The ideal candidate is a hands-on engineer who enjoys working across AI, application development, data, and cloud engineering. You should be comfortable working in an evolving environment, taking ideas from an initial concept to a production-ready solution, and collaborating with both technical and non-technical stakeholders.

Strong communication, ownership, technical curiosity, and the ability to work through ambiguous problems are important for success in this role.