About the role
Simulmedia - Lead AI Engineer — Agentic Products & Platform Lead AI Engineer — Agentic Products & Platform Lviv, Kyiv Engineering – Engineering / Full-time / Hybrid apply for this job
About
the Role Simulmedia is building AI into how TV advertising is planned, activated, and measured. This role is for the engineer who builds it. You are a strong backend engineer who has gone deep on AI and agentic systems: someone as comfortable designing a production service architecture as reasoning about LLM context windows, tool use, and agent failure modes. You will own the design, implementation, and ongoing reliability of Simulmedia's agentic AI products, working across Product, Data Science and Engineering teams to bring these systems to life. You are the technical owner of Simulmedia's AI systems: the person who drives how they are built, how they behave in production, and how the rest of
the team builds around them. This is a lead individual contributor role with broad technical influence. You are not managing a team. You are the person others look to when the question is how do we actually build this.
What You'll Own Agentic AI Products Design and build AI agents embedded in the product across campaign management, workflow automation, audience intelligence, and other areas on the roadmap Own the full engineering stack for each agent: tool definitions, orchestration logic, context management, output validation, guardrails, and human-in-the-loop design Translate product and data science intent into working, observable, production-grade agentic systems Set the technical patterns and reference implementations that the broader engineering team builds around AI Platform and Integration Layer Build and own the shared infrastructure that agentic features run on: LLM API integration, prompt management, agent memory and state, evaluation harnesses Define the interfaces between agentic systems and the rest of the platform: how agents consume data, trigger actions, and return results to product surfaces Work with Data Engineering to ensure agents have access to the right data at the right latency from the Databricks pipeline Work with Full Stack engineers to surface agent capabilities in product UIs, APIs, and integrations: you own the backend contract, they own the surface Reliability and Observability for AI Systems Define what healthy looks like for an agentic system and instrument accordingly: response quality, latency, failure rates, fallback behavior Build evaluation pipelines to catch regressions before they reach users Own incident response for AI system failures, including participation in 24/7 on-call rotation: you understand the system well enough to diagnose and fix quickly Cross-functional Technical Collaboration Be the go-to technical resource for Data Scientists who want to embed their models and outputs into product workflows: not owning the models, but owning the engineering that makes them usable in production Help Full Stack and Data Engineering teams build AI-aware features confidently, by establishing clear patterns and being available to unblock them Document decisions, patterns, and system designs so
