AI Engineer

We are looking for a Full Stack AI Engineer to join a growing engineering team focused on building intelligent, enterprise-grade applications using Generative AI, modern software engineering, and cloud technologies.

This is an opportunity to work on new AI-driven products and capabilities from the ground up, helping transform how employees and customers access information, complete workflows, make decisions, and interact with technology. The engineer will contribute across the full development lifecycle from identifying business opportunities and designing solutions to implementation, deployment, and ongoing optimization.

• Design and develop scalable applications that incorporate Generative AI, Large Language Models (LLMs), automation, and advanced analytics.
• 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 Dev Ops 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.

• 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, Type Script, 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.

• Experience building RAG (Retrieval-Augmented Generation) or enterprise knowledge-retrieval solutions.
• Familiarity with vector databases, embeddings,…