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Atlys is building an AI-first platform to remove friction from global travel. The company has processed visas for 1M+ travelers across 127 countries and is still in early growth stages.
As Product Manager - AI, you will drive execution of complex technical initiatives spanning Engineering, Product, AI, and Operations teams. This is a high-ownership role focused on bringing structure to ambiguity, aligning cross-functional stakeholders, and delivering programs with measurable business impact.
Key responsibilities include:
- Build AI evaluation systems: Define success metrics for real-world tasks, construct benchmarks and evaluation frameworks, and establish regression testing to measure quality, reliability, and user outcomes.
- Improve agent harnesses: Work on context management, memory systems, tool calling, orchestration, retry logic, and failure recovery to increase AI system reliability and capability.
- Drive AI from experimentation to production: Own AI initiatives end-to-end, making informed trade-offs across model selection, prompting strategies, retrieval augmentation, fine-tuning, reinforcement learning, latency optimization, and cost efficiency.
- Leverage production data for continuous improvement: Identify failure modes using production data and edge cases, design experiments, and iteratively improve model and system performance.
- Execute cross-functionally: Partner with AI, Engineering, Product, and Operations teams to define roadmaps, establish success metrics, and build reliable production systems.
The role requires someone who thrives in fast-moving environments, enjoys solving complex execution challenges, and can build scalable systems to accelerate shipping and operational efficiency.
REQUIREMENTS:
- 4–7 years of experience as a Technical Program Manager (TPM), Engineering PM, or similar execution-focused role, ideally with AI/ML exposure including reinforcement learning (RL) and evaluation frameworks
- Demonstrated leadership of complex cross-functional technical programs involving AI/ML teams
- Highly structured and detail-oriented mindset; ability to bring clarity to ambiguous situations
- Strong analytical and data-driven approach, using metrics (model accuracy, latency, business KPIs) to prioritize and improve execution
- Exceptional communication skills with ability to influence without direct authority across technical, business, and AI/ML teams
