AI & Agentic Workflows Product Owner

Auxis; Colombia; On-site; COP 120,000,000 - 180,000,000; Full time

Job summary

Auxis is seeking an AI-focused Product Owner to drive end-to-end product ownership and hands-on technical execution for AI and agentic initiatives. The role spans ideation, backlog, architecture alignment, and deployment within a complex enterprise setting.

The candidate will own AI/agentic solution design, Python development, API integrations, and governance, collaborating with senior staff on high- complexity architecture decisions and ensuring value realization.

Qualifications

• 2–4 years delivering software or AI-enabled solutions.
• Hands-on experience with AI or agentic capabilities in production or substantial proof‑of‑concept.
• Proficiency in Python for AI/agent development.
• Knowledge of LLM orchestration, prompt design, tool calling, RAG.
• Experience with APIs, data integration and system integration.
• Git/GitHub workflows, code review, and CI/CD.
• Ability to translate business problems into technical and product solutions.
• Strong documentation and stakeholder management skills.

Responsibilities

• Own the lifecycle of AI and agentic initiatives from ideation to delivery, adoption, and continuous improvement.
• Define product objectives, success metrics, and roadmaps aligned to business priorities.
• Lead discovery to identify AI/process improvement opportunities.
• Translate business needs into product artifacts (statements, user stories, acceptance criteria).
• Manage and prioritize product backlogs based on value, risk, and readiness.
• Track outcomes like efficiency gains, cycle-time reduction, and cost savings.
• Design and build AI/agentic solutions across technologies (agents, LLM orchestration, RAG, APIs).
• Develop, deploy, and iterate on AI agents with defined scope, tools, memory, and guardrails.
• Build evaluation harnesses and monitoring for agent quality and responsible AI.
• Evaluate AI approaches and tools; consult senior staff on design decisions.
• Develop in Python for AI orchestration and data processing; write integration scripts.
• Work with relational and vector data; write queries for AI logic and reporting.
• Design and consume APIs for system-to-system communication.
• Collaborate with data/analytics/governance to embed models responsibly.
• Configure, test, and deploy AI/agentic solutions using Agile; ensure governance.
• Collaborate with platform, security, and infra for reliability and compliance.
• Maintain documentation, version control, testing strategies, and handoff.
• Manage GitHub workflows (branches, PRs, code review, CI/CD).
• Support AI governance and lifecycle management; monitoring/observability.
• Serve as primary liaison between business, tech teams, and leadership; communicate direction, risks, and results.
• Lead adoption, training, and rollout planning; provide guardrails for citizen developers.

Skills

Product ownership

Backlog prioritization

Stakeholder management

Agile delivery

Problem-to-technical translation

Tools

Python

GitHub

API design

CI/CD

Job description

This role blends product ownership with hands‑on technical execution: owning a product’s lifecycle from opportunity discovery and backlog definition through solution design, build, testing, deployment, and value realization.

Operating within a complex enterprise environment, the Product Owner combines product thinking, stakeholder engagement, and applied development skills. This role independently advances AI initiatives from concept to production, selecting and applying appropriate AI, agentic, LLM-orchestration, integration, and application technologies to solve real business problems, while collaborating with senior technical staff on higher‑complexity architecture decisions.

Key Responsibilities

Product Ownership & Delivery

• Own the lifecycle of assigned AI and agentic initiatives, from ideation and intake through delivery, adoption, and continuous improvement.
• Define product objectives, success metrics, and roadmaps aligned to business strategy and operational priorities.
• Lead discovery efforts to identify opportunities for process improvement and AI and agentic enablement.
• Translate business needs into clear product artifacts, including problem statements, user stories, acceptance criteria, workflow models, and value hypotheses.
• Manage and prioritize product backlogs based on value, risk, complexity, and organizational readiness.
• Track and communicate outcomes such as efficiency gains, cycle‑time reduction, cost savings, quality improvements, and compliance benefits.

AI & Agentic Technical Execution

• Design and build AI and agentic solutions across a range of technologies, including:
  • AI agents and autonomous / multi‑agent workflows
  • LLM orchestration, prompt / instruction design, and tool / function calling
  • Retrieval‑augmented generation (RAG) and knowledge / context integration
  • AI‑assisted decisioning and human‑in‑the‑loop processes
  • API‑driven integrations and service orchestration
  • Low‑code / no‑code and custom application development
• Develop, deploy, and iterate on AI agents and agentic workstreams — defining agent scope, instructions, tools, memory, and evaluation criteria, with appropriate human oversight and safety guardrails.
• Build evaluation harnesses, guardrails, and monitoring for agent quality, reliability, and responsible‑AI compliance.
• Evaluate and recommend AI and agentic approaches and tools based on use case, risk profile, and long‑term sustainability, consulting senior staff on higher‑complexity design decisions.

Application Development & Integration

• Develop in Python for AI and agent orchestration, automation logic, data processing, and integration scripting, following modular, testable, and maintainable coding practices.
• Work with relational, structured, and vector data sources; write queries and build data interactions to support AI logic, retrieval, and reporting.
• Design and consume APIs and services to enable system‑to‑system communication and scalable agentic workflows.
• Partner with data, analytics, and governance teams to incorporate models, insights, and AI capabilities into solutions responsibly.

Agile Delivery & Governance

• Configure, develop, test, and deploy AI and agentic solutions using Agile methodologies and established (or to‑be‑defined) processes.
• Partner with platform, security, and infrastructure teams to ensure solutions meet enterprise standards for reliability, compliance, and scalability.
• Ensure proper documentation, version control, evaluation / testing strategies, and operational handoff are in place.
• Manage source control and collaborative development in GitHub, including branching, pull requests, code review, and CI / CD workflows.
• Support AI governance, model and agent lifecycle management, and monitoring / observability for deployed agents.
• Serve as a primary point of contact between business stakeholders, technical teams, and leadership for assigned initiatives.
• Communicate product direction, tradeoffs, progress, risks, and results clearly and confidently.
• Lead adoption and change enablement activities, including training, documentation, and rollout planning.
• Support business‑led or citizen‑developed solutions by providing guardrails, guidance, and technical oversight.

Required Qualifications

• 2–4 years delivering software, automation, data, or AI‑enabled solutions in a professional environment, with demonstrated recent hands‑on experience applying AI or agentic capabilities (production or substantial proof‑of‑concept).
• Hands‑on experience (production or substantial proof‑of‑concept) building, deploying, or integrating AI capabilities such as large language models and AI‑assisted workflows, including exposure to AI agents or agentic workstreams.
• Proficiency in Python for AI and agent development, scripting, and data processing.
• Working knowledge of LLM orchestration concepts such as prompt / instruction design, tool / function calling, retrieval‑augmented generation (RAG), and evaluation.
• Experience working with structured and/or vector data, APIs, and system integration.
• Fluency with Git / GitHub for version control, branching, pull requests, code review, and collaborative development.
• Ability to translate business problems into technical and product solutions.
• Strong documentation, communication, and stakeholder‑management skills.