Lead - Engineer AI/ML, Azure, Python, Next.js/React at Zenoti

Hyderabad, Telangana, India -

Full Time

Start Date

Immediate

Expiry Date

26 Jan, 26

Salary

0.0

Posted On

28 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Next.js, React, AI/ML, Azure, Cloud Automation, REST APIs, GraphQL, Microservices, SQL, NoSQL, Docker, Kubernetes, CI/CD, MLOps, Generative AI

Industry

Software Development

Description

Zenoti provides an all-in-one, cloud-based software solution for the beauty and wellness industry. Our solution allows users to seamlessly manage every aspect of the business in a comprehensive mobile solution: online appointment bookings, POS, CRM, employee management, inventory management, built-in marketing programs and more. Zenoti helps clients streamline their systems and reduce costs, while simultaneously improving customer retention and spending. Our platform is engineered for reliability and scale and harnesses the power of enterprise-level technology for businesses of all sizes Zenoti powers more than 30,000 salons, spas, medspas and fitness studios in over 50 countries. This includes a vast portfolio of global brands, such as European Wax Center, Hand & Stone, Massage Heights, Rush Hair & Beauty, Sono Bello, Profile by Sanford, Hair Cuttery, CorePower Yoga and TONI&GUY. Our recent accomplishments include surpassing a $1 billion unicorn valuation, being named Next Tech Titan by GeekWire, raising an $80 million investment from TPG, ranking as the 316th fastest-growing company in North America on Deloitte’s 2020 Technology Fast 500™. We are also proud to be recognized as a Great Place to Work CertifiedTM for 2021-2022 as this reaffirms our commitment to empowering people to feel good and find their greatness. To learn more about Zenoti visit: https://www.zenoti.com We are looking for a passionate Full Stack Developer with expertise in AI/ML, Azure, Python, Next.js/React, and cloud automation to design and build scalable, cloud-native applications. You will work on both front-end and back-end systems, integrate AI/ML models, and contribute to automation-driven product development. Key Responsibilities Develop full stack applications with Python (backend) and Next.js/React (frontend). Build, deploy, and optimize AI/ML models in production using Azure ML and related services. Design and implement REST/GraphQL APIs, microservices, and cloud-native solutions. Work on infrastructure & cloud automation projects (Azure DevOps, IaC with Terraform/Bicep/ARM templates). Leverage Azure cloud services (App Services, Functions, AKS, Cosmos DB, Blob Storage). Ensure performance, security, and scalability of applications. Collaborate with cross-functional teams in an Agile environment. Required Skills Strong programming in Python (Django/FastAPI/Flask). Experience with AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn). Proficiency in React.js/Next.js. Hands-on experience with Azure Cloud & automation (Azure DevOps, IaC tools, Kubernetes). Strong knowledge of SQL & NoSQL databases. Familiarity with Docker, Kubernetes, CI/CD pipelines. Nice to Have Experience with MLOps practices and Generative AI (LLMs, LangChain, etc.). Knowledge of serverless and event-driven architectures. Education Bachelor’s/Master’s in Computer Science, Engineering, or related fields. Zenoti provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

Responsibilities

Develop full stack applications using Python for the backend and Next.js/React for the frontend. Build and optimize AI/ML models in production while designing cloud-native solutions.