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 Responsibilities3.1 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, InsurTech, or other data-heavy domains a strong plus 5. Preferred Background & Experience5.1 Must-Have * 2–5 years of experience in product management, project management, or a closely related role * Demonstrated experience owning delivery for software products, ideally in a startup or small-team environment * Familiarity with LLM-based systems (prompt design, evaluation, RAG patterns, or similar) from a PM or technical background * Proficiency in English (written and spoken) — will participate in U.S. team standups and documentation * Available for real-time collaboration until at least 11:00 AM PST on a consistent basis * Based in Kyiv and able to work from the Ceres office
5.2 Strongly Preferred * Prior experience working on or alongside AI/ML features; LLM-specific PM experience highly valued * Experience in AgTech, InsurTech, FinTech, or any domain with structured geospatial or time-series data * Exposure to agentic AI frameworks (LangGraph, CrewAI, Anthropic MCP) or RAG architectures * Familiarity with Salesforce CRM workflows, satellite/weather data products (Sentinel-2, ERA5, NDVI), or parametric insurance logic * Track record of defining evaluation frameworks for probabilistic AI outputs * Public product writing, talks, or open-source contributions a plus
5.3 Educational Background * Bachelor’s or Master’s degree in Computer Science, Engineering, Business, Data Science, or equivalent * Equivalent demonstrated experience (strong portfolio of shipped products / written specs) accepted in lieu of formal degree
6. Working Norms & Collaboration * Based in the Kyiv * Real-time overlap with U.S. Pacific Time until 11:00 AM PST on a consistent basis * Weekly 1:1 with U.S. Product/Science leadership; daily async standups in Slack * Work tracked via Jira; specs maintained in Confluence ; all artifacts version-controlled * Documentation-first culture — every greenfield feature begins with a brief product/technical spec before implementation * Each feature ships with: defined success criteria, an evaluation approach (especially for probabilistic outputs), and an agreed observability hook * Milestone-based deliverables tied to agreed 2-week sprint cycles
7. Hiring Process * Application Resume + 2-paragraph cover note: why Ceres AI, why you. * Intro / Background Interview — 30 min Discussion of previous experience, product thinking, cross-functional collaboration, and communication style. * Technical / Workflow Interview — 45–60 min Discussion of product requirements, workflow ownership, delivery approach, and ability to work with technical teams. * Collaboration & Values Fit — 30 min Discussion of working style, ownership mindset, communication expectations, and team fit. * Offer & Contract Full-time offer issued with a 30-day probationary onboarding period aligned with Sprint 1.
8. Benefits & Perks * Medical insurance. * Mobilization protection support * Hybrid / on-site work * Collaborative international team. * Real impact: shape the future of AI in agriculture.
