1. Role Overview
Ceres AI builds data-driven tools for agriculture and agribusiness, combining advanced imagery, climate analytics, and machine learning to help customers make smarter decisions about risk, operations, and outcomes. Our platform serves agricultural lenders, insurers, and growers across multiple geographies.
This is a hands-on role for someone equally comfortable writing requirements and owning delivery. The PM will serve as the primary product and project point of contact within the Kyiv office, working closely with a small, highly capable engineering team locally and collaborating asynchronously with product, science, and commercial teams in the U.S. Over time the portfolio expands to support Ceres’ core product base alongside the greenfield AI track.
2. Engagement Structure
Type
Full-time employee
Location
Kyiv, Ukraine — real-time overlap with U.S. Pacific Time required (available until 11:00 AM PST)
Start
15 June 2026
Duration
Long-term engagement; portfolio scope expands as platform matures
Compensation
Salary based on experience and interview performance.
3. Primary Responsibilities
3.1 Product Ownership
Define and maintain the product vision, requirements, and roadmap for greenfield AI features, with an initial focus on LLM-based capabilities and the agentic platform
Translate ambiguous research questions and business opportunities into clear, actionable product specs
Prioritize features and iterations based on technical feasibility, user feedback, and business impact
Conduct discovery with internal stakeholders and—over time—external customers to validate product direction
3.2 Project & Delivery Management
Own end-to-end delivery for the assigned feature portfolio, from sprint planning through production release
Manage day-to-day execution with the Kyiv engineering team; keep work unblocked and on track
Monitor project status and communicate progress clearly to both local and U.S.-based stakeholders
Identify risks early and drive resolution without waiting to be asked
3.3 Experimentation & Iteration
Run fast experimentation cycles—lightweight prototyping and validation—to test LLM and AI concepts before committing to full builds
Define success criteria and evaluation approaches for AI features where outputs are probabilistic or hard to measure objectively
Maintain a tight feedback loop between early results and product direction
3.4 Cross-Functional Collaboration
Serve as the primary product and project point of contact within the Kyiv office
Collaborate asynchronously with U.S.-based product, science, and commercial teams; provide real-time overlap during morning U.S. hours
Contribute to roadmap planning and sprint reviews with both local and distributed stakeholders
4. Required Skills & Knowledge
The following matrix reflects the core competencies evaluated during the hiring process:
Product Management
2–5 years owning end-to-end software delivery in a startup or small-team environment; comfortable with both product definition (requirements, prioritization, discovery) and delivery (sprint management, risk tracking) without a hard boundary between the two
AI / LLM Familiarity
Practical understanding of LLM-based systems — prompt design, evaluation, RAG patterns, or similar — from either a PM or technical background
Delivery & Agile
Strong working knowledge of Agile methodologies; fluency with Jira, Linear, Confluence, Notion, or equivalent
Technical Acumen
Able to engage substantively in technical tradeoffs and architecture discussions; not required to write code, but expected to hold own in technical conversations
Communication
Strong written and verbal English; clear, concise, low-noise async communication; participates in U.S. team standups and documentation
Analytical Thinking
Low tolerance for ambiguity in specs; clear sense of what matters and what does not; comfortable with probabilistic outputs
Domain Familiarity
Background in AgTech, FinTech, Ins
