Dev AI Architect & Team Lead
Chargebee · Chennai
- Experience10–11 yrs
- SalaryNot disclosed
- Work modeonsite
- Posted28 Sept 2026
About Chargebee
Chargebee is hiring in Chennai in technology software. This role looks for around 10+ years of experience.
Skills
- Python
- large language models
- agentic workflows
- prompt engineering
- API design
- CI/CD
- data governance
- AI safety
- distributed systems
- SaaS architecture
- vector databases
- Retrieval-Augmented Generation
- fine-tuning
- software engineering
The role
A generative AI engineering architect at a subscription software company designs production AI systems using generative AI engineering, large language models, and agentic workflows, while guiding secure model deployment. The role also applies data governance and API design to scalable internal automation.
Full job description
About ChargebeeChargebee is a leading provider of billing and monetization solutions, empowering businesses with recurring revenue models to streamline revenue and finance operations, capture actionable insights, and drive growth. Chargebee is trusted by businesses of all sizes, including Zapier, LegalZoom, Lambda, Freshworks, DeepL, Condé Nast, and Pret a Manger, and is proud to have been consistently recognized by customers as a Leader in Subscription Management on G2.With headquarters in North Bethesda, Maryland, our team members are based primarily in India, the U.S., and Europe.
About the TeamThe AI Center of Excellence is a collaborative group of specialists dedicated to integrating advanced Intelligence into our core operational workflows. We focus on building scalable, production-grade AI systems that drive measurable impact across the organization. Our team values technical rigor, cross-functional partnership, and a commitment to ethical AI practices.
About the roleAs the Dev AI Architect and Team Lead, you will serve as a hands-on technical authority responsible for building and scaling our internal AI capabilities. You will define the technical vision for the team, architecting robust frameworks that leverage large language models and agentic workflows. In this role, you will mentor a dedicated group of engineers to deliver high-impact, secure, and governable AI solutions.
What you'll do• Define the technical roadmap and architecture for production-grade AI systems and agentic frameworks.• Lead and mentor a team of engineers, fostering a culture of technical excellence and continuous learning.• Design and implement scalable LLM integrations and prompt engineering strategies to solve complex business problems.• Oversee the development of robust API designs and CI/CD pipelines tailored for AI-driven applications.• Collaborate with stakeholders to identify high-ROI opportunities for AI automation within the engineering lifecycle.• Establish data governance and AI ethics standards to ensure secure and compliant model deployment.• Architect data engineering pipelines that support real-time AI inference and long-term model monitoring.• Drive the adoption of best practices in software engineering for AI, ensuring code quality and system reliability
What you'll bring• 10+ years of professional experience in software engineering, with a significant focus on distributed systems or SaaS architecture.• Bachelor's degree in Computer Science, Engineering, or a related technical field.• Extensive experience architecting and deploying AI-driven applications using Python and modern LLM frameworks.• Proven track record of building and managing high-performing engineering teams in a technical lead capacity.• Expertise in designing and maintaining secure API layers and integrated CI/CD environments.• Deep understanding of data governance, privacy standards, and AI safety protocols in a cloudenvironment.• Demonstrated ability to implement agentic workflows and autonomous AI agents in production settings.• Experience with vector databases, RAG (Retrieval-Augmented Generation) architectures, and fine-tuning methodologies.
Nice to have• Experience with advanced model evaluation frameworks and automated red-teaming for LLMs.• Previous experience working within high-growth B2B SaaS environments.• Familiarity with MLOps platforms and automated hyperparameter tuning at scale.• Active contributions to open-source AI projects or technical research communities