Were looking for a hands-on AI Engineering Tech Lead to define and drive AI-native engineering practices, lead the architecture and development of scalable, intelligent systems, and embed AI across the software development lifecycle. This role involves providing technical leadership, identifying and solving architectural challenges, and collaborating cross-functionally to deliver high-impact, production-grade solutions.
Responsibilities:
Define and codify AI-native engineering practices, patterns, and guidelines to elevate the software development lifecycle.
Provide technical leadership and mentorship, fostering an AI-first engineering culture across teams.
Architect and lead the development of AI-native system frameworks that emphasize modularity, extensibility, and adaptive scalability.
Identify architectural risks, systemic bottlenecks, and long‑term scalability concerns - and proactively drive solutions.
Collaborate closely with Product, Customer success, Security and Business stakeholders to ensure technical solutions deliver real business impact.
Requirements: Requirements
Hands-on experience (6y+) with distributed systems, microservices, and cloud-native technologies.
Proven ability to leverage AI-assisted engineering to drive operational excellence, from generating robust test suites to automating the detection of scalability bottlenecks in distributed systems.
A pragmatic mindset that balances engineering excellence with business needs.
Strong proven technical skills building features end-to-end and passion for large-scale production services, data modeling and databases.
Strong experience with AWS/Azure/GCP and a passion for building highly observable, resilient systems.
Strong communication skills, empathetic, and someone who thrives working in a fast-paced environment.
Prior experience in deploying and maintaining a high scale, multi-region production-grade system.
Advantages
Experienced in B2B Cyber Security / Cloud Security / Identity & Access Management / Encryption Keys Management.
Deep understanding of the Kubernetes ecosystem and modern platform engineering practices.
Hands-on experience building or integrating AI agents and workflows.
This position is open to all candidates.