Full-Stack Developer

At Sequoia Connect we are a Talent-First Technology Ecosystem that redefines how elite professionals interact with the global digital landscape. We move beyond traditional models to act as a catalyst for the top 1% of global talent connecting human potential with complex industrial execution. By joining our inner circle you are not simply taking a position; you are aligning with a strategic partner dedicated to updating your Human OS and accelerating your growth through world-class high-impact projects.

We are currently partnering with a rapidly growing automation-led powerhouse that serves 31 Fortune 500 companies across the financial healthcare and manufacturing sectors. With a global workforce of over 32000 employees and a presence in 28 countries our client is a titan of digital transformation. Their Automate Everything Cloudify Everything strategy ensures you will be working at the absolute forefront of AI-driven automation and cloud solutions.

This is your chance to thrive in a Customer Success First and Always environment that prizes continuous learning and radical ownership. You will collaborate within an international network of expertise across 39 delivery centers worldwide gaining exposure to complex engineering challenges that redefine industrial standards. If you are a driven professional looking for a dynamic forward-thinking workplace where your growth is the priority this is where you belong.

We are currently searching for a Full-Stack Developer:

Responsibilities

• Build end-to-end products taking full ownership from backend API architecture to frontend UI development.
• Develop integrate and maintain production-grade machine learning pipelines (ML) with a specific focus on Natural Language Processing (NLP) applications.
• Design and implement fast reliable and scalable model inference APIs.
• Manage data processing workflows to ensure optimal performance of ML models in production.
• Deploy applications using AWS or cloud-agnostic methodologies managing containerization and continuous integration/continuous deployment.

Requirements

• Core Development: Strong expertise in building user interfaces with React and developing backend APIs using Python and FastAPI.
• AI/ML Integration: Proven expertise working with Python-based Machine Learning (ML) pipelines especially Natural Language Processing (NLP).
• Infrastructure & Deployment: Hands-on experience with AWS or cloud-agnostic deployment (e.g. ECS/Fargate Docker).
• DevOps: Solid experience setting up and managing CI/CD pipelines.
• Architecture: Strong understanding of data processing scalable architecture and exposing model inference APIs.
• High-Performance Mindset: Resilience emotional intelligence and a focus on agile delivery.
• Technologist DNA: A deep understanding of the difference between coding and engineering (knowing how to productionize and scale an ML model not just run it in a notebook).

Desired

• Familiarity with cloud-native foundations or AI coding assistants.

Languages

• Advanced Oral English.
• Advanced Spanish.

Note:

• Fully remote.

If you meet these qualifications and are pursuing new challenges start your application on our website to join an award-winning employer. Explore all our job openings Sequoia Careers Page:
AI Developer Generative AI LLM Core RAG Vector Database Azure OpenAI FastAPI Machine Learning MLOps Semantic Search Backend Engineer.

Requirements:

• Core Development: Strong expertise in building user interfaces with React and developing backend APIs using Python and FastAPI.
• AI/ML Integration: Proven expertise working with Python-based Machine Learning (ML) pipelines especially Natural Language Processing (NLP).
• Infrastructure & Deployment: Hands-on experience with AWS or cloud-agnostic deployment (e.g. ECS/Fargate Docker).
• DevOps: Solid experience setting up and managing CI/CD pipelines.
• Architecture: Strong understanding of data processing scalable architecture and exposing model inference APIs.
• High-Performance Mindset: Resilience emotional intelligence and a focus on agile delivery.
• Technologist DNA: A deep understanding of the difference between coding and engineering (knowing how to productionize and scale an ML model not just run it in a notebook).