Technical Product Owner | GenAI Delivery (Mid-level)

Provectus is a Premier AWS Partner and an Anthropic partner featured in Forrester's AI Technical Services Landscape. We are roughly 420 engineers building production AI for enterprise clients in Financial Services Healthcare and Life Sciences Retail and Entertainment. We build custom systems on live client data not off the shelf products and not demos. We are opening a Solution Owner seat on our Delivery team in Colombia and Costa Rica. This is an early career seat but it is not a training seat. You will sit between the client and the engineering team on a real engagement own a slice of scope and be expected to figure out the next step yourself. The profile we are looking for is specific you started technical as a software data or ML engineer and you have already moved toward the business side of building products or you are ready to make that move now. You are the person on the team who automates their own work with AI tools before anyone asks.

What You Will Do

Own a defined slice of a client engagement from use case framing through backlog release and result Run discovery sessions and workshops with client stakeholders and turn what you hear into written scope engineers can build against Translate technical constraints into business language and business goals into technical requirements Maintain a groomed backlog with sized technically specific stories and drive sprint planning and release cadence Prototype rapidly on live client data using our delivery stack including Claude Claude Code MCP servers and

Skills

Work alongside GenAI and agentic AI builds including RAG agent workflows and LLM integrations closely enough to judge quality and explain trade offs Define success metrics for your slice of scope and report progress honestly including when something is not working Build reusable artifacts demos and documentation so the next engagement starts faster than yours did Partner with Principal Architects Forward Deployed Engineers and account teams across US and LATAM time zones What You Will Bring 2 to 4 years of total professional experience including hands on engineering time as a software data or ML engineer At least 1 year in a product delivery or client facing role such as Product Owner Technical Product Owner Business Analyst Delivery Lead or equivalent Daily use of GenAI tools in your own workflow Claude and Claude Code preferred with concrete examples of workflows you redesigned Ability to read code and technical documentation well enough to hold a real conversation with senior engineers Practical Agile and Scrum experience backlog sprints planning retrospectives Written and spoken English at B2 or above comfortable leading a client call without a manager in the room Self direction as a default. You are given a goal and ambiguity not a task list and you move anyway Based in Colombia or Costa Rica

Nice to Have

Exposure to Financial Services and Insurance or Healthcare and Life Sciences clients Working understanding of GenAI concepts prompt engineering RAG embeddings vector databases agentic patterns Familiarity with AWS especially Bedrock SageMaker Lambda or S3 Experience shipping an LLM or RAG feature that reached real users Experience building your own automations scripts MCP integrations or internal tools Consulting or professional services background Certifications such as CSPO SAFe PO/PM or AWS Cloud Practitioner

What We Offer

Real client delivery on frontier AI from month one not shadowing Direct access to Principal Architects and Forward Deployed Engineers as your working peers Anthropic and AWS partnership work with early access to tooling and premium AI subscriptions Internal training programs and full support for AWS and Claude certifications A clear growth path toward Senior Solution Owner or Solutions Architecture Remote work with flexible hours across US and LATAM overlap Long term B2B collaboration Equipment budget and all the tooling you need We may use artificial intelligence (AI) tools to support parts of the hiring process such as reviewing applications analyzing resumes or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed please contact us.