Ruby on Rails Developer (AI Focused)

A fast-growing US-based SaaS company is transforming how energy firms manage operations. Their end-to-end ERP platform streamlines field data, production, finance, land, and compliance, delivering real-time insights and operational efficiency. With a strong client base and innovative tech, they’re redefining digital transformation in the energy and utilities sector. You’ll design and implement AI-driven functionality that improves automation and user experience. This includes leveraging LLMs, machine learning models, and modern AI tooling within a production SaaS environment. This is a hands-on role for someone who can move quickly, make pragmatic decisions, and bring AI concepts into real, scalable product features.

Responsibilities

Design and implement AI-powered features within the platform (e.g., automation, recommendations, copilots); Integrate LLMs and/or ML models into existing services and workflows; Evaluate, select, and optimize AI tools, APIs, and frameworks for production use; Collaborate with Product to translate business problems into AI-driven solutions; Build and maintain scalable backend services to support AI functionality; Profile, test, and optimize performance of AI-integrated systems; Ensure reliability, security, and cost-efficiency of AI components in production; Contribute to architecture decisions around AI integration and system design; Partner with engineering teams to embed AI into existing applications without degrading stability

Requirements

Years of experience: 3 to 5 years; 3+ years of experience as a software engineer in a SaaS or cloud-based environment; Strong backend engineering experience (RoR and/or Golang preferred); Experience integrating APIs and working within distributed systems; Hands-on experience with AI/ML tools (e.g., OpenAI, Anthropic, Hugging Face, or similar); Experience building or integrating AI-powered features into applications (not just experimentation); Strong understanding of data flow, system design, and performance optimization; Experience with relational databases (SQL Server or similar); Familiarity with microservices architecture, Kubernetes, and CI/CD pipelines; Experience deploying applications in Azure or similar cloud environments; Strong problem-solving skills with ability to work in ambiguous, fast-moving environments; Builder mindset—someone who can take an idea and turn it into a working feature quickly; Pragmatic approach to AI (focus on value, not hype); Ability to work independently in a contract environment while collaborating closely with internal teams; Strong communication skills and ability to explain AI concepts to non-technical stakeholders

Nice to have

Experience with prompt engineering, embeddings, or retrieval-augmented generation (RAG); Exposure to model evaluation, fine-tuning, or AI performance monitoring; Experience with event-driven architectures or real-time data processing; Background in energy, fintech, or other complex data-driven industries