✈️ Senior Technical Developer (AI & ML Infrastructure)

📍 Remote | Latin America
💼 Contractor Agreement | Full-Time
🌎 Hiring Company: Allied Global
🗣️ Language Requirements: Advanced English (B2+/C1)

Allied Global is seeking a Senior Technical Developer to join an innovative engineering team building a production-ready SaaS platform used by enterprise clients to manage large-scale capital and construction projects.

This is not a traditional Full Stack role. In addition to building modern web applications, you'll help develop the company's AI and Machine Learning infrastructure, including a custom fine-tuned Large Language Model (LLM) specialized in construction project controls and a voice AI platform that enables field teams to interact with the system through speech.

You'll work directly with the founder and engineering leadership to build production-grade software and AI capabilities that support mission-critical decisions worth millions of dollars. If you're passionate about modern web development, Machine Learning, and solving complex technical challenges, this is an opportunity to make a significant impact while expanding your expertise in production AI systems.

• Design, develop, and maintain scalable enterprise web applications using modern technologies.
• Build responsive user interfaces with React and Next.js (App Router).
• Develop backend services and type-safe APIs using TypeScript.
• Design and optimize PostgreSQL databases using advanced SQL (raw SQL, CTEs, window functions, schema design, and migrations).
• Participate in software architecture discussions and technical decision-making.
• Write clean, maintainable, and well-tested production code following engineering best practices.

• Help build the company's custom Machine Learning infrastructure supporting production AI systems.
• Contribute to the development and continuous improvement of a fine-tuned Large Language Model (LLM) specialized for construction project controls.
• Develop Python-based ML pipelines for data preparation, model training, fine-tuning, evaluation, and inference.
• Participate in LLM fine-tuning using technologies such as PyTorch, Hugging Face, Transformers, and PEFT/LoRA.
• Support the development of voice AI solutions, including Speech-to-Text (STT) and Text-to-Speech (TTS) pipelines for field-facing AI interactions.
• Collaborate on domain-specific model evaluation frameworks to improve model accuracy, reliability, and performance.
• Contribute to GPU-based training and inference optimization, including model serving, quantization, and performance tuning.

• Work closely with the founder, product, and engineering teams in an Agile environment.
• Participate in code reviews and technical design discussions.
• Troubleshoot production issues and continuously improve system reliability and performance.
• Collaborate across teams to deliver scalable, high-quality software solutions.

• 3+ years of professional experience with TypeScript in production environments.
• Strong experience building applications with React.
• Experience with Next.js App Router, including server components, route handlers, and middleware.
• Strong SQL skills using PostgreSQL (raw SQL).
• Professional experience using Python for backend development or Machine Learning workflows.
• Experience developing type-safe APIs (REST or frameworks such as tRPC).
• Experience with Git, pull request workflows, and collaborative software development.
• Strong analytical, debugging, and problem-solving skills.
• Experience working in Agile development environments.
• Strong written and verbal English communication skills (B2+/C1).
• Ability to quickly learn new technical domains and adapt to evolving AI technologies.

Experience with any of the following is highly valued:

• Hands-on experience with Large Language Models (LLMs).
• PyTorch, Hugging Face, Transformers, PEFT, or LoRA.
• Model fine-tuning, evaluation, and ML experimentation.
• Building or maintaining ML pipelines.
• Voice AI technologies (Speech-to-Text / Text-to-Speech).
• GPU infrastructure, CUDA, or GPU resource monitoring.
• Model serving, inference optimization, quantization, or high-throughput inference systems.
• Experience working with production AI systems—not just prompt engineering or API integrations.

• Tailwind CSS.
• Modern component libraries (such as Radix UI).
• Interactive dashboards and data visualization.
• Report generation (PDF, Excel, Word, or PowerPoint).

• Docker and containerized applications.
• CI/CD pipelines.
• Testing frameworks (unit and integration testing).
• Self-hosted deployments or container orchestration.

• Experience building Enterprise SaaS platforms.
• Exposure to construction, engineering, industrial, or project management software.
• Interest in combining modern Full Stack development with Machine Learning infrastructure.