GenAI Engineer at FusionHit

, , Mexico -

Full Time

Start Date

Immediate

Expiry Date

02 Feb, 26

Salary

0.0

Posted On

04 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Software Engineering, LLM Development, GenAI Systems, Prompt Engineering, Plugin Orchestration, AWS Infrastructure, LangChain, Ray, Multi-Modal Systems, Speech Recognition, Natural Language Understanding, Computer Vision, Real-Time Voice Synthesis, Systems-Thinking, Observability, Communication Skills

Industry

IT Services and IT Consulting

Description

At FusionHit, we are driven by a clear vision—to empower organizations with AI‑centered solutions that make them more adaptable, efficient, and future‑ready. As a company at the forefront of innovation, we help our clients build exceptional software that not only meets today’s needs but anticipates tomorrow's challenges. Our approach blends cutting‑edge AI technology, top‑tier talent acquisition, and expert project management to ensure that businesses can scale effectively and deliver high‑quality, world‑class software on time and within budget. Our partnerships speak volumes, with clients like Instructure, Young Living, Imagine Learning, Mars Corp., and many others trusting us to lead the way in software development. We are rapidly growing across our offices in the US, LATAM, and India, and we're creating an environment where talented individuals can thrive, collaborate, and have fun while building transformative solutions. If you're excited by the opportunity to work in a fast‑paced, innovative environment where scaling and building the future of software is key, we’d love to hear from you. Join us as we work together to redefine the world of software development! Location:Location: Must reside and have work authorization in Latin America. Availability:Availability: Must be available to work with significant overlap with Mountain Standard Time (MST). Independent Contractor Agreement - Direct hire with our partner based in the US. Project Overview: We are partnering with a pioneering client at the forefront of immersive learning and AI‑powered simulations. Their platform enables professionals to practice and master complex interpersonal skills in high‑stakes environments using cutting‑edge technology that blends Large Language Models (LLMs), speech recognition, natural language understanding, computer vision, and real‑time voice synthesis. What makes this project unique is its combination of human‑in‑the‑loop orchestration with advanced multi‑modal AI systems—bringing together live interactions, avatar control, and scalable LLM infrastructure to deliver incredibly lifelike and impactful training experiences. This is a mission‑driven environment backed by research in learning science, psychology, and AI. The goal is to scale this system into a production‑grade platform that consistently delivers predictable, stable, and low‑latency GenAI performance. If you’re passionate about building enterprise‑level LLM infrastructure, working across complex AI systems, and helping shape the future of human‑AI interaction—this is a rare and high‑impact opportunity. The Ideal Candidate Has: BS/MS in Computer Science, Information Technology, or related field with 5+ years of experience in software engineering. 2+ years focused specifically on LLM/GenAI system development and deployment. Proven experience scaling LLMs from R&D into production with strong attention to reliability and performance. Deep understanding of prompt engineering, plugin orchestration, and agent-based frameworks. Proficiency with AWS infrastructure—SageMaker, Lambda, EKS/ECS, DynamoDB. Experience with orchestration and deployment tools like LangChain, Ray, or similar LLMOps frameworks. Familiarity with real-time multi-modal systems involving speech, vision, or avatar interfaces. Systems-thinking mindset with a strong commitment to maintainability and observability. Excellent communication skills in English (C1 preferred, strong B2 may be considered). Key Responsibilities: Architect and scale production-grade LLM systems with a focus on reliability, latency, and predictability. Design and implement LLM orchestration systems, including plugin APIs and agent workflows. Optimize and support multi-modal GenAI components such as voice, NLP, and visual modules. Manage cloud infrastructure on AWS (SageMaker, Lambda, EKS/ECS, DynamoDB). Monitor and ensure LLM service performance using observability and monitoring tools. Translate R&D models into robust, enterprise-ready AI products. Contribute to platform architecture and roadmap planning. Mentor team members and promote a collaborative engineering culture.

Responsibilities

Architect and scale production-grade LLM systems with a focus on reliability, latency, and predictability. Design and implement LLM orchestration systems, including plugin APIs and agent workflows.