SINAI is a San Francisco–based climate technology company helping enterprises measure, analyze, and reduce carbon emissions. Our platform supports complex reporting, modeling, and regulatory workflows that enable companies to meet ambitious decarbonization targets.
We value ownership, collaboration, and pragmatic execution. We look for people who enjoy solving real-world problems, making thoughtful tradeoffs, and shipping reliable software in a fast-moving environment.
The Role
We’re hiring a
mid-level AI Engineer
to help build and integrate AI-powered features into our platform, with a strong focus on Large Language Models (LLMs).
In this role, you’ll work closely with Software Engineers, Product Managers, and Data-focused teammates to design, implement, and operate AI-driven capabilities. You won’t be defining company-wide AI strategy, but you will have meaningful ownership over implementation details, experimentation, and production quality.
This is a hands-on role focused on turning AI capabilities into reliable, customer-facing features.
What You’ll Do
Design, build, and integrate
LLM-powered features
into SINAI’s platform
Implement and iterate on AI-driven workflows that improve user experience and automate processes
Evaluate and compare AI models to determine fit for specific product use cases
Help deploy, monitor, and operate AI/ML features in production environments
Collaborate with Engineering and Product to translate requirements into working AI solutions
Contribute to experimentation, prototyping, and incremental improvement of AI capabilities
Stay current with new tools, models, and best practices in applied AI
Required Qualifications
3+ years of professional software engineering experience , ideally in data-heavy or backend systems
1+ year of hands-on experience
integrating LLMs into real applications (production or near-production)
Experience working with modern AI models and APIs (e.g., OpenAI, Anthropic, Meta, or similar)
Strong coding skills in
Python
or
TypeScript/JavaScript
Familiarity with AI/ML libraries or frameworks (e.g., LangChain, Hugging Face, PyTorch, TensorFlow)
Experience deploying and supporting services in a cloud environment (AWS, GCP, or Azure)
Solid problem-solving skills and ability to work effectively with partial requirements
Professional proficiency in written and spoken
English
Nice to Have
Experience integrating OpenAI or similar APIs in a production environment
Familiarity with
vector databases
and retrieval-augmented generation (RAG) patterns
Exposure to AWS AI/ML services (e.g., Bedrock, SageMaker)
Experience improving user workflows using AI or automation
Experience working in SaaS products or startup environments
Interest in climate, sustainability, or data-intensive domains