We’re looking for a talented AI-native Software Engineer to join our innovative R&D team!
Voyantis helps its customers acquire better users and spend less doing it - and our core team owns the engine behind it. We turn raw customer data into ad-network conversions, end-to-end: through large-scale ML and data pipelines, event-driven delivery services on AWS, and the UI that ties it together. There's no narrow lane here - you own problems wherever they live in the stack.
We're an AI-native team: we treat AI and agentic tooling as a first-class part of how we build, and it's how a small team credibly owns this much surface area. We're looking for a high-ownership generalist who works this way (or is hungry to), and who thrives in a correctness-critical domain where a bug means real customer ad-spend going the wrong way.
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
Turn raw customer data into ad-network conversions end to end, building across the whole stack: ML and data pipelines, delivery services, and the customer-facing UI.
Take features from idea to production largely on your own, designing, shipping, monitoring, and iterating, using AI and agentic tooling as a force multiplier, and owning your systems in production where mistakes translate directly into customer spend.
Collaborate closely with the team lead, product, and data scientists to take models and ideas from prototype to reliable, scaled-up production.
Requirements
3+ years of hands-on experience building production cloud systems end to end: architecture, development, testing, and cloud-native work in production.
Strong Python (our primary language), and solid software engineering foundations: software design principles, concurrency, data structures, and cost/performance trade-offs.
An AI-native, can-do generalist: you use (or are eager to adopt) AI and agentic tooling as a core part of how you ship, you're comfortable across the whole stack and unafraid of unfamiliar territory, and you take strong ownership of systems end to end on a small team.
A team player with excellent communication skills, strong independent-learning ability, and curiosity to explore new fields and constantly improve.
Advantage:
SQL and modern data warehouses (Snowflake, BigQuery or Databricks equivalent).
Experience with ad-network, martech, attribution, or measurement ecosystems (Google Ads, Meta, MMPs, conversion APIs).
Experience with modern cloud and orchestration tooling: Temporal, Airflow, Docker, Kubernetes, ArgoCD, Terraform, and AWS.
Background in analytics, data science, or product: you think like an analyst or PM about what makes a signal correct and valuable, not just whether the code runs. We value this highly.
3+ years of hands-on experience building production cloud systems end to end: architecture, development, testing, and cloud-native work in production.
Strong Python (our primary language), and solid software engineering foundations: software design principles, concurrency, data structures, and cost/performance trade-offs.
An AI-native, can-do generalist: you use (or are eager to adopt) AI and agentic tooling as a core part of how you ship, you're comfortable across the whole stack and unafraid of unfamiliar territory, and you take strong ownership of systems end to end on a small team.
A team player with excellent communication skills, strong independent-learning ability, and curiosity to explore new fields and constantly improve.
Advantage:
SQL and modern data warehouses (Snowflake, BigQuery or Databricks equivalent).
Experience with ad-network, martech, attribution, or measurement ecosystems (Google Ads, Meta, MMPs, conversion APIs).
Experience with modern cloud and orchestration tooling: Temporal, Airflow, Docker, Kubernetes, ArgoCD, Terraform, and AWS.
Background in analytics, data science, or product: you think like an analyst or PM about what makes a signal correct and valuable, not just whether the code runs. We value this highly.
