Senior AI Engineer – LLMs, Agentic AI

Applaudo

Senior AI Engineer building production-grade LLM and agentic AI solutions at Applaudo. Collaborating across teams to optimize AI capabilities and workflows.

Posted 7/29/2026full-timeRemote • 🇨🇴 ColombiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in building and maintaining LLM and agentic AI applications, integrating models like Anthropic and OpenAI into production environments, and optimizing AI systems through best engineering practices. Proficient in Python, SQL, and MLOps methodologies, with a strong focus on collaboration and problem-solving.

Highest-signal resume keywords

Python ProficiencySQL SkillsLLM Application DevelopmentMLOps PracticesPrompt Engineering

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

PythonSQLLLM DevelopmentPrompt EngineeringIntent ClassificationContext ManagementMulti-Step OrchestrationAI Performance OptimizationEvaluation FrameworksNatural Language Processing

Soft Skills

CollaborationCommunicationProblem-Solving

Tools & Technologies

AnthropicOpenAICloud Data WarehousesGPU AccelerationHugging FaceVector DatabasesRetrieval-Augmented Generation

Certifications & Qualifications

AWS Certification

Industry Keywords

MCP ServersAI SolutionsTool CallingFallback StrategiesCost OptimizationCI/CDObservabilityReproducible PipelinesConversational AIClient-Facing AI Products

Tech Stack

Tools & technologies

AWSCloudPythonSQL

About the role

Key responsibilities & impact

Build and maintain MCP servers, tool definitions, and context management capabilities.
Design and implement intent evaluation, classification, and routing workflows.
Integrate Anthropic and OpenAI models into production environments.
Manage prompt versioning, fallback strategies, and LLM performance optimization.
Develop and maintain evaluation frameworks to validate model quality and production performance.
Collaborate closely with software engineers and AI specialists to deliver production-ready AI solutions.
Participate in architecture discussions and contribute to AI platform design.
Continuously improve AI systems through experimentation, optimization, and engineering best practices.

Requirements

What you’ll need

Bachelor’s Degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a related field is desired, or equivalent professional experience.
Strong proficiency in Python and software engineering best practices.
Strong SQL skills working with cloud data warehouses.
Hands-on experience building production-grade LLM and agentic AI applications.
Experience implementing tool calling, MCP servers, context management, and multi-step orchestration.
Experience integrating hosted LLM APIs such as Anthropic and OpenAI into production environments.
Experience with prompt engineering, prompt versioning, fallback strategies, and cost/latency optimization.
Experience designing intent classification and routing solutions for natural language applications.
Experience building conversational AI solutions or multi-API orchestration workflows.
Experience developing LLM evaluation methodologies and working within existing codebases.
Strong collaboration, communication, and problem-solving skills.
Professional English proficiency.
Nice to Have: Experience deploying, fine-tuning, and evaluating open-source models using Hugging Face.
Experience with GPU acceleration and inference optimization.
Experience implementing MLOps practices, including CI/CD, observability, and reproducible pipelines.
Experience with vector databases and Retrieval-Augmented Generation (RAG).
Applied NLP experience.
Experience building client-facing AI products.
AWS certification.

Benefits

Comp & perks

All your information will be kept confidential according to EEO guidelines.