The DevOps Engineer will deploy and manage Kubernetes systems, build CI/CD pipelines, optimize service meshes, and automate tasks using scripting.

Lead development of automation frameworks for AI/ML applications, ensuring reliability and scalability of LLM-based products while optimizing CI/CD integrations and performance testing.

The Senior Implementation Consultant will manage implementation for enterprise customers, design and deploy AI solutions, lead discussions, and ensure project documentation and efficiency improvements.

The Technical Customer Success Manager is responsible for client onboarding, ongoing support, troubleshooting, relationship management, and product training, ensuring clients optimize their use of AI virtual agents.

As an SDE III - Backend, you will design, develop, and optimize backend systems, working closely with teams to build scalable services using Java and Spring Boot while implementing modern technologies and best practices.

Lead the design of user experiences for conversational AI across channels, optimizing for clarity and user engagement while aligning with business goals.

The DevOps Engineer will manage cloud infrastructure, automate deployments, and optimize application performance while ensuring system uptime and reliability.

Design and develop Android applications, collaborating with teams to implement new features, maintain code quality, and optimize performance.

The Program Manager will oversee cross-functional program delivery, manage team coordination, ensure customer implementations, and report on project governance while driving operational excellence.

The SDE I - Frontend role involves owning UI modules, building reusable components, collaborating with engineers, and ensuring optimal UI performance.

The iOS Developer will design and build applications for iOS devices, ensuring quality and responsiveness, while collaborating with teams to integrate new features.

The AI Automation Engineer will create automated systems for testing and enhancing conversational AI models using Python, integrating LLMs and developing pipelines for quality evaluation, monitoring, and compliance.

Lead UX design initiatives for AI-centric features, conduct user research, and collaborate with teams to enhance product functionality and user experience.

Develop and maintain scalable data pipelines, perform data analysis, and collaborate with teams to support data-driven decisions. Mentor junior engineers.

Craft and optimize prompts for AI performance. Collaborate with teams to deliver customized solutions, evaluate metrics, and stay updated on NLP advancements.

The Senior Implementation Consultant configures and implements SaaS solutions, leads customer engagements, manages projects, and drives efficiencies in delivery.

Lead quality assurance across engineering and customer-facing functions, establish quality strategy, and ensure product reliability and security for AI-driven SaaS platform.

The SDET will test AI-based products, improve quality assurance processes, and provide feedback to enhance AI models. Responsibilities include manual and automation testing and API testing.

The SDET II will focus on ensuring product quality, conducting manual and automated testing, and improving QA processes for AI-based products.

The role involves testing AI conversational products, improving quality assurance processes, and providing feedback for enhancing model accuracy.