AI Tech Lead (AI Engineering)

TL;DR

AI Tech Lead (AI Engineering): Leading AI-driven initiatives to improve engineering velocity and system reliability for a high-availability video platform with an accent on AI tooling adoption and production-grade ML solutions. Focus on building AIOps capabilities, optimizing incident response, and integrating AI/ML into cloud-native distributed systems on AWS.

Location: Hybrid (Offices in New York, London, Singapore, and Tel Aviv)

Company

hirify.global is a global leader in the video market, providing a cloud-based platform that powers live, on-demand, and real-time video experiences for over 1000 organizations worldwide.

What you will do

• Lead AI-driven initiatives across M&T engineering, from initial scoping and architecture to hands-on execution.
• Drive the adoption of AI tooling and practices across Dev and DevOps teams both within the department and cross-organizationally.
• Identify opportunities where AI can enhance engineering velocity, incident response, cost efficiency, and system reliability.
• Collaborate with group managers and engineers to translate AI capabilities into practical, production-grade solutions.
• Evaluate emerging AI tools, frameworks, and approaches to keep the technology stack current.

Requirements

• 7+ years of software engineering experience, with at least 3 years focused on AI/ML in production environments.
• Hands-on experience with backend services, APIs, microservices, and DevOps (CI/CD, infrastructure, cloud operations).
• Proven track record of building or integrating AI/ML solutions in cloud-native, distributed systems, preferably on AWS.
• Strong understanding of observability concepts, including metrics, logs, traces, alerting, and anomaly detection.
• Experience driving technical initiatives across multiple teams without direct authority.
• Excellent communication skills to translate complex AI concepts for non-AI engineers.

Nice to have

• Experience with LLMs, RAG pipelines, or AI agents applied to engineering operations (AIOps).
• Familiarity with Kubernetes, Grafana, or similar operational tooling.
• Background in media tech, video streaming, or telecom platforms.
• Experience with Databricks, MLflow, or similar ML platform tooling.

Culture & Benefits

• Hybrid and flexible work environment.
• Extended private health insurance, including mental health coverage.
• Personal and professional development programs.
• Occasional cross-company long weekends.