Senior AI Engineer (LLMs & Agentic AI)

Applaudo Studios

1d•Remote

About The Position

You are a Senior AI Engineer passionate about building production-grade LLM applications and agentic AI systems. You thrive in collaborative environments where you design, implement, and optimize AI capabilities that power conversational experiences and intelligent workflows. You enjoy solving complex AI challenges, integrating cutting-edge LLM technologies, and continuously improving production systems through experimentation, evaluation, and engineering best practices.

Requirements

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.
Senior-level experience building production AI applications with Python and LLM technologies.
Experience designing and deploying conversational AI or agentic AI solutions.
Strong experience with prompt engineering, LLM integrations, and evaluation methodologies.
Availability to work remotely with overlapping business hours.

Nice To Haves

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.

Responsibilities

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.