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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