At RemoteStar, 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