Position Level: Mid-Level

Position Overview

As a Mid-Level AI Engineer at Raincode, you will be assigned to client projects as part of our staff augmentation and delivery services, working either on-site or remotely depending on client needs. You will design, develop, and integrate AI/ML solutions that address real business challenges for our clients, particularly in the Scandinavian market. This role requires hands-on experience with modern AI frameworks and the ability to build end-to-end AI pipelines, from data ingestion to production deployment. You will collaborate closely with client stakeholders, translate business requirements into AI-driven solutions, and contribute to knowledge sharing within Raincode.

Key Responsibilities

• Collaborate with client stakeholders to gather requirements, define success metrics, and align AI solutions with business objectives

• Design and develop machine learning models and AI systems (NLP, computer vision, recommendation systems, etc.) using frameworks such as TensorFlow, PyTorch, or scikit-learn

• Build and maintain data pipelines for structured and unstructured data, including ETL processes, data cleaning, and feature engineering

• Implement and optimize inference services and microservices for model deployment using tools such as Docker, Kubernetes, or serverless architectures

• Integrate third-party AI tools and APIs (e.g., OpenAI, AWS SageMaker, Azure Cognitive Services, Hugging Face) into web and mobile applications

• Monitor, evaluate, and improve model performance in production environments, including retraining and fine-tuning to meet performance and SLA requirements

• Follow software engineering best practices including version control (Git), CI/CD pipelines, testing, and documentation

• Document AI architectures, APIs, workflows, and best practices for both client and internal use

• Mentor junior engineers in AI best practices, coding standards, and business-oriented solution design

• Maintain professional communication with client stakeholders and represent Raincode with technical excellence and integrity

Required Qualifications

• Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, Software Engineering, or a related field (or equivalent practical experience)

• 3–5 years of professional experience in AI/ML engineering or a closely related role

• Strong proficiency in Python and libraries such as NumPy, Pandas, scikit-learn, TensorFlow, or PyTorch

• Experience with NLP techniques (e.g., transformers, embeddings, LLM integrations) and/or computer vision frameworks

• Familiarity with cloud ML services (AWS, GCP, or Azure) and containerization/orchestration tools such as Docker and Kubernetes

• Hands-on experience integrating third-party AI APIs and services

• Solid understanding of software engineering best practices, including Git workflows, CI/CD, and unit testing

• Ability to translate business requirements into measurable AI solutions

• Strong communication skills and confidence in client-facing environments, including presenting technical concepts to non-technical stakeholders

Preferred Qualifications

• Experience with MLOps tools such as MLflow, Kubeflow, or TFX

• Knowledge of data visualization tools and libraries (Matplotlib, Plotly, Dash)

• Background in prompt engineering and prompt-tuning strategies

• Exposure to edge AI or IoT-based AI deployments

• Familiarity with Agile or Lean methodologies

Growth Path

Typical timeline to Senior AI Engineer: 2–3 years, depending on performance and client impact. Advancement is based on successfully delivering production-grade AI solutions, demonstrating ownership of end-to-end AI systems, receiving strong client feedback, mentoring junior team members, and contributing to Raincode’s AI strategy and best practices.