Vacancies

Customer’s country  — The USA

Candidate Location: The position can be performed remotely from Ukraine, with the option to work from or occasionally visit the company’s office in Lviv

Compensation Structure: The developers do not have a fixed salary. Instead, you receive a base rate that is paid regardless of whether they are assigned to a project. In addition, they receive project-based compensation ranging from $2,500 to $3,500 per project.

Most projects are for different clients and are considered full-time engagements. However, since many of them are not highly complex or particularly time-consuming, developers often work on multiple projects simultaneously. As a result, it is quite common for developers to be assigned to two projects at the same time.

Start & Duration: Long-term cooperation

Working Hours: Full alignment with the EST time zone is required. This is not just a few hours of overlap — candidates are expected to work the full EST schedule to ensure availability for client meetings and project-related communication

Interview Stages:

A 2-minute candidate video introduction

Hiring Manager Interview

Technical Interview (System Design + AI/Data Engineering discussion + live coding)

About the Company & Project

The client’s company is a New York and Virginia — headquartered AI, Data, and Full-Stack Engineering firm delivering advanced software and intelligent systems to businesses across the United States.

We specialize in building AI-driven platforms, scalable data infrastructure, and cloud-native applications that power modern digital products. Our engineering teams focus on LLM-powered applications, data engineering pipelines, MLOps platforms, and modern web architectures for startups and enterprise clients.

Due to growing demand for AI transformation and data-driven platforms, we are expanding our engineering team with high-performing AI, Data, and MLOps engineers who are comfortable working in client-facing environments and motivated by performance-based earning opportunities.

Key Responsibilities

AI Engineering

• Design and implement LLM-powered applications and AI workflows
• Build AI agent systems, RAG pipelines, and intelligent automation
• Integrate OpenAI, Anthropic, or open-source models (Llama, Mistral, etc.)
• Develop AI-powered product features such as recommendations, document processing, and decision systems

Data Engineering

• Build data ingestion and transformation pipelines
• Design data lake and data warehouse architectures
• Implement streaming and batch processing pipelines
• Work with technologies such as Spark, Kafka, Airflow, and modern data platforms

MLOps & AI Infrastructure

• Deploy and manage machine learning models in production
• Build ML pipelines, model monitoring, and automated training workflows
• Implement model evaluation and experiment tracking systems
• Design scalable AI infrastructure on AWS, GCP, or Azure

Full-Stack Engineering

• Develop scalable backend services (Python, Node.js)
• Build modern frontend applications (React / Next.js / TypeScript)
• Implement microservices architectures and API platforms
• Integrate AI capabilities into production web applications

Cloud & DevOps

• Deploy applications on AWS, Kubernetes, or serverless infrastructure
• Build CI/CD pipelines and automated deployment workflows
• Design secure and scalable multi-tenant systems

Required Qualifications

• 5 – 8+ years of software engineering experience
• Strong experience in AI Engineering, Data Engineering, or Machine Learning
• Experience building cloud-native systems
• Strong system design and distributed systems knowledge
• Experience with Python or Node.js backend development
• Familiarity with MLOps tools and data pipelines
• Excellent English communication skills
• Comfortable working with US-based clients
• Strong ownership mindset and professionalism

Preferred Experience

• LLM integrations and generative AI applications
• RAG pipelines and vector databases
• Machine learning model deployment
• Data platform architecture
• Multi-tenant SaaS systems
• Microservices and event-driven architectures

Prior experience in consulting or client-facing engineering roles