Senior AI Engineer - LATAM
This position offers you the opportunity to join a fast-growing technology organization that is redefining productivity paradigms in the software engineering industry. Thanks to our flexible, distributed model of global operation and the high caliber of our experts, we have enjoyed triple digit growth over the past five years, creating amazing career opportunities for our people.
If you want to accelerate your career working with like-minded subject matter experts, solving interesting problems and building the products of tomorrow, this opportunity is for you.
Parser is seeking an experienced AI Engineer to join our innovative team. The ideal candidate will have a strong background in building production-ready AI systems, with a focus on agentic AI and large language models.
Purpose
Design, architect, and implement scalable Generative AI frameworks and tools. This role will focus on enabling non-engineers and junior developers to create NLP- and document-generation solutions through low-code or no-code interfaces, while also contributing to the company's AI technology strategy alongside the Tech and Engineering Leadership teams.
Key Responsibilities
- Architect and implement a GenAI framework to enable internal teams to build and deploy document processing and NLP solutions with minimal coding effort.
- Lead the design and configuration of low-code/no-code AI development environments, integrating Azure OpenAI and Microsoft Cognitive Services.
- Define and implement AI architecture patterns, reusable components, and governance standards for scalable AI adoption.
- Collaborate with Tech Leaders and Engineering Leads to shape the AI technology roadmap, identifying opportunities for innovation and efficiency through GenAI.
- Build proofs of concept (POCs) that demonstrate new GenAI capabilities—such as document summarization, text generation, or automated content workflows.
- Support integration between GenAI tools and existing .NET-based systems, APIs, and enterprise data sources.
- Define AI model lifecycle standards including prompt engineering, versioning, data sourcing, and quality validation.
- Contribute to technical strategy discussions around model selection, cloud infrastructure, and tool evaluation.
- Coach and support engineers and business stakeholders in adopting and extending GenAI-based solutions.
Core Skills & Experience
1. Generative AI & NLP Expertise
- Proven experience implementing solutions using Azure OpenAI Service (GPT 3.5/4) or similar LLMs.
- Strong understanding of prompt design, embeddings, fine-tuning, and RAG (Retrieval-Augmented Generation) workflows.
- Experience building document-centric AI applications, including summarization, classification, redaction, or content generation.
- Familiarity with vector databases and semantic search pipelines for contextual data retrieval.
- Hands-on experience designing LLM-based architectures that combine generative reasoning with structured data.
2. Framework Architecture & Low-Code Enablement
- Experience defining AI frameworks, SDKs, or internal developer tools for reusable AI capabilities.
- Proven experience with low-code/no-code platforms such as Power Automate, Power Apps, Logic Apps, or other workflow orchestration tools.
- Ability to integrate LLM capabilities into enterprise environments, balancing scalability, maintainability, and usability.
- Understanding of prompt orchestration, pipeline automation, and governance controls for GenAI systems.
3. Microsoft Ecosystem & Development
- Deep familiarity with Microsoft Azure services:
- Azure OpenAI Service
- Azure Cognitive Search
- Azure AI Studio / Azure Machine Learning
- Azure Functions, Azure Logic Apps, and Azure DevOps
- Strong experience developing or integrating APIs in .NET (C#).
- Working knowledge of Python for prototyping or building orchestration scripts (preferred but not required).
- Understanding of data integration, security, and compliance within Microsoft environments.
4. Strategic & Collaborative Experience
- Experience contributing to technology strategy, architecture decisions, or enterprise AI roadmaps.
- Ability to evaluate and recommend emerging tools and frameworks for GenAI adoption.
- Skilled at collaborating with Engineering Leads, Tech Leaders, and business stakeholders to align AI capabilities with organizational objectives.
Preferred Qualifications
- Experience building AI-powered documentation, knowledge management, or content generation systems.
- Familiarity with AI governance, responsible AI principles, and data privacy frameworks.
- Microsoft Certified: Azure AI Engineer Associate (AI-102) or equivalent certification.
- Exposure to RAG frameworks such as LangChain, Semantic Kernel, or Azure AI Studio orchestration.
Soft Skills
- Strategic mindset with the ability to balance innovation and practicality.
- Excellent communication and presentation skills for both technical and non-technical audiences.
- Strong sense of ownership and accountability in delivering high-impact solutions.
- Collaborative, proactive, and comfortable working in evolving technical environments.
