Job Summary

Grant Thornton is building an AI Factory to deliver enterprise‑grade, agentic AI solutions that move beyond pilots into sustained business impact. As an AI Engineer, you will be a core builder within a cross‑functional AI Pod, responsible for implementing, testing, and deploying agentic systems into real client workflows. This role is hands‑on and execution‑focused.

You will turn architectural designs and product intent into reliable, observable, and production‑ready AI components, working closely with the AI Product Lead, Lead AI Architect, and Automation Engineers.

Responsibilities

Agentic System Development

Build and implement agentic AI components, including:

Tool‑using agents

Multi‑step reasoning and execution flows

Planner, executor, and validator agent patterns

Translate architectural designs into working, maintainable code

Ensure agent behavior is bounded, predictable, and aligned with intent

Prompt, Memory & Retrieval Engineering

Develop prompts as versioned, testable software artifacts

Implement and tune

Retrieval‑augmented generation (RAG)

Memory and context‑management strategies

Input and output constraints

Optimize prompts and retrieval for accuracy, latency, and cost

Evaluation, Testing & Reliability

Build evaluation harnesses to assess:

Accuracy and relevance

Hallucination and failure rates

Regression across prompt and model changes

Implement automated testing and validation for AI workflows

Partner with the Lead AI Architect to monitor drift and degradation over time

Deployment & Operations

Package and deploy AI components into production environments

Integrate AI logic into APIs, services, and workflows





Instrument solutions for

Performance

Usage

Cost‑to‑serve

Support production troubleshooting and iterative optimization

Collaboration Within the AI Pod

Work closely with

AI Product Lead to align implementation with acceptance criteria

Lead AI Architect on design decisions and patterns

Automation / Integration Engineers to enable real‑world execution

Contribute to reusable components, templates, and patterns within the AI Factory

Skills and Experience

- English - Spanish Language (Oral and writing B2+ or above).
- Bachelor’s degree in computer science, Engineering, or a related field is desirable.
- Minimum of 5 years of experience in AI, automation, or a related field.
- Proficiency in UiPath and MS Power Automate, or similar automation platforms.
- Strong understanding of UiPath architecture and its components, with experience in server administration (Windows and Linux) and cloud environments (Azure, AWS).
- Proficiency with cloud platforms such as AWS, Azure, or GCP, particularly for deploying and managing UiPath Orchestrators.
- Experience with data analysis and reporting tools like MS Power BI.
- Experience with database management (SQL Server, Oracle).
- UiPath Certified Professional Advanced RPA Developer (UiARD) Certification is required.



Additional certifications in cloud platforms (AWS, Azure) are highly desirable.
- Strong leadership abilities with a focus on mentoring junior engineers.
- Excellent analytical, problem-solving, and troubleshooting skills.
- Collaborative mindset with the ability to work effectively across cross-functional teams.
- Adaptability to changing circumstances, learning new technologies, and driving continuous improvement.
- High integrity and ethical standards in professional conduct.

About

Auxis

Experience

4–8+ years of experience in software engineering, data engineering, or applied AI development

Hands‑on experience building and deploying systems into production environments

Comfort working in agile, fast‑moving delivery teams

AI & Agentic Skills

Practical experience with

Generative AI and LLMs

Agentic frameworks or orchestration patterns

Tool calling and action execution

Strong understanding of common LLM failure modes and mitigation techniques

Ability to reason about when to rely on AI vs deterministic logic

Technical Skills

Strong proficiency in Python

Experience with

API development and integration

Event‑driven or workflow‑based systems

CI/CD and modern DevOps practices

Familiarity with cloud‑native architectures (Azure preferred)

Preferred Qualifications

Experience implementing

Retrieval‑augmented generation (RAG)

Vector databases and embedding strategies

Exposure to monitoring, observability, or MLOps concepts

Experience working in enterprise or regulated environments

Consulting or client‑facing delivery experience

📌 AI Engineer (Bogotá)
🏢 Auxis
📍 Bogotá