Ruby on Rails Developer (AI Focused) USA

Remotestar

Houston (TX)

Hybrid

USD 100,000 - 130,000

Full time

14 days+

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Job summary

RemoteStar is seeking a Software Engineer to enhance their AI capabilities in Houston, TX. The role involves designing and implementing AI-driven features within a growing SaaS platform. Candidates should have over 3 years of experience in backend engineering, particularly with RoR or Golang, and familiarity with ML tools. Strong problem-solving skills and the ability to work independently in a quick-moving environment are essential. This hands-on position requires a builder mindset to turn ideas into features rapidly.

Qualifications

  • 3+ years of experience as a software engineer in a SaaS or cloud-based environment.
  • Hands-on experience with AI/ML tools like OpenAI, Anthropic, or Hugging Face.
  • Strong understanding of performance optimization in distributed systems.

Responsibilities

  • Design and implement AI-powered features within the platform.
  • Integrate LLMs and/or ML models into existing services.
  • Collaborate with Product to solve business problems using AI.

Skills

Backend engineering
AI/ML tools
API integration
Data flow understanding
Problem-solving skills

Tools

RoR
Golang
SQL Server
Kubernetes
Azure

Job description

AtRemoteStar, we're currently hiring for one of our clients based in Houston, TX.

Years of experience: 3 to 5 years

Location: USA

About Client

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
  • 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
Preferred
  • 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
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