Description :

We are looking for a Tech Lead to drive the end-to-end technical design and development of AI powered B2B SaaS products. This role requires a strong hands-on technologist who can work closely with ML Engineers and Full Stack Development teams, own the product architecture, and ensure scalability, security, and compliance across the platform.

Responsibilities :

- Lead the end-to-end architecture and development of AI-driven B2B SaaS products.

- Collaborate closely with ML Engineers, Data Scientists, and Full Stack Developers to integrate AI/ML models into production systems.

- Define and own the overall product technology stack, including backend, frontend, data, and cloud infrastructure.

- Design scalable, resilient, and high-performance architectures for multi-tenant SaaS platforms.

- Drive cloud-native deployments (Azure) using modern DevOps and CI/CD practices.

- Ensure data privacy, security, compliance, and governance (SOC2 GDPR, ISO, etc. ) across the product.

- Take ownership of application security, access controls, and compliance requirements.

- Actively contribute hands-on through code reviews, complex feature development, and architectural POCs.

- Mentor and guide engineering teams, setting best practices for coding, testing, and system design.

- Work closely with Product Management and Leadership to translate business requirements into technical solutions.

Requirements :

- 5 to 10 years of overall experience in software engineering and product development.

- Strong experience building B2B SaaS products at scale.

- Proven expertise in system architecture, design patterns, and distributed systems.

- Hands-on experience with cloud platforms (AWS / Azure / GCP).

- Solid background in backend technologies (Python/. NET/Node.js/Java) and modern frontend frameworks like React, JS, etc.

- Experience working with AI/ML teams and deploying ML models into production environments.

- Strong understanding of data security, privacy, and compliance frameworks.

- Experience with microservices, APIs, containers, Kubernetes, and cloud-native architectures.

- Strong working knowledge of CI/CD pipelines, DevOps, and infrastructure as code.

- Excellent communication and leadership skills with the ability to work cross functionally.

- Experience in AI-first or data-intensive SaaS platforms.

- Exposure to MLOps frameworks and model lifecycle management.

- Experience with multi-tenant SaaS security models.

- Prior experience in product-based companies or startups.