We are seeking a hands-on, business-oriented DevOps Team Lead to spearhead our infrastructure and cloud operations. You will build and maintain the foundational systems enabling our agentic AI ecosystem while leading a team of talented engineers to translate technical capabilities into commercial impact.
Our core technology uses advanced AI predictive models (LTV, churn, and intent). You will ensure the high-performance infrastructure required for autonomous signal engineering and real-time recalibration of these models is optimized for performance and ROI.
In this role, you will bridge the gap between infrastructure excellence and business strategy, ensuring our technical roadmap is optimized for both performance and ROI.
About Us
Voyantis was founded in 2020 on the premise that market fundamentals are shifting companies worldwide from growth-at-all-costs strategies to efficient and responsible growth practices, with a focus on improving Unit Economics. With a bold mission to leverage AI to reimagine the whole Growth process, to streamline this transition and ensure its sustainability, Voyantis eliminates the guesswork from customer value creation, empowering leaders with actionable strategies and tactics to acquire, nurture and retain the high-value customers their businesses really need, with the actions and the timing that would be most impactful to achieve their goals.
Leading companies like Miro, Rappi and Moneylion rely on Voyantis to effectively apply these predictions. They use Voyantis to drive high-value customer acquisition on platforms like Google and Meta, optimize incentives through Salesforce and Braze, and perfectly time upsells, resulting in a 20%-40% ROI uplift.
Voyantis is well-backed by top VCs such as Target Global and SquarePeg. The company has tripled in size annually over the past two years and now boasts a team of 100 with offices in California, New York and Tel Aviv.
Responsibilities
Leadership & Hands-on Execution: Manage and mentor a high-performing DevOps team while remaining deeply involved in technical execution, architecture, and troubleshooting.
AI-Driven SDLC: Continue evolving our software development lifecycle by integrating AI-driven methodologies and agentic AI tools to automate delivery, improve code quality, and accelerate release cycles.
Infrastructure Management: Own and optimize our core cloud infrastructure on AWS and our data warehouse environment on Snowflake.
Resource Management & ROI: Take accountability for the cloud infrastructure budget. Monitor costs, manage vendor relationships (SaaS & AI tooling), and ensure all resource allocations drive tangible business value.
Security & Compliance: Enforce rigorous security standards and data privacy protocols across all infrastructure and engineering workflows to protect our product ecosystem.
Requirements
6+ years in DevOps/Infrastructure roles, with at least 2 years in a leadership or team lead capacity.
Expert-level experience with AWS services and modern cloud-native architectures.
Demonstrated hands-on experience managing and optimizing Snowflake environments.
Proven ability to make infrastructure decisions based on commercial impact, cost-efficiency, and user growth.
Strong proficiency in IaC (Terraform/Pulimi), CI/CD pipelines, container orchestration (K8s), and integrating AI/ML models into production workflows.
Ability to articulate complex infrastructure postures and budget rationales to both technical and non-technical stakeholders.
6+ years in DevOps/Infrastructure roles, with at least 2 years in a leadership or team lead capacity.
Expert-level experience with AWS services and modern cloud-native architectures.
Demonstrated hands-on experience managing and optimizing Snowflake environments.
Proven ability to make infrastructure decisions based on commercial impact, cost-efficiency, and user growth.
Strong proficiency in IaC (Terraform/Pulimi), CI/CD pipelines, container orchestration (K8s), and integrating AI/ML models into production workflows.
Ability to articulate complex infrastructure postures and budget rationales to both technical and non-technical stakeholders.
