Founding AI Engineer
Role Overview
Aeris Dynamics is not a software company, we build and operate real-world systems. This role exists to embed AI directly into those operations.
We are seeking a Founding AI Engineer to serve as the first dedicated software engineering hire at Aeris Dynamics. This role will anchor a new digital products function within our Technical Department.
You will lead the development and scaling of two core platforms:
Cold Chain Intelligence (CCI)
Aeris Control Tower (ACT)
In parallel, you will implement Generative AI (GenAI) solutions across the enterprise, embedding AI into real workflows to improve productivity and unlock new value.
This is a hands-on, production-focused role. You will take AI-driven prototypes into fully deployed systems, establish engineering standards, and work closely with domain experts and external partners.
Key Responsibilities
Design, build and deploy GenAI features (classification, extraction, summarization, drafting, agent workflows)
Embed AI into live business workflows with proper evaluation, observability and guardrails
Architect and develop scalable full-stack systems for CCI and ACT
Convert AI prototypes into secure, production-grade applications
Own Google Cloud infrastructure (Cloud Run, Cloud SQL, Firebase), including deployment, CI/CD, scaling, security and cost
Integrate third-party APIs (IoT, logistics, weather, geolocation, messaging) reliably at scale
Provide technical oversight of external development partners and uphold engineering standards
Build and manage data pipelines, analytics systems and ML-driven improvements
Leverage AI coding tools to accelerate delivery while maintaining engineering quality
Requirements
Must-Have
Proven experience deploying GenAI/LLM-powered features in production (e.g. RAG, copilots, agents, classification)
3 years of full-stack development experience (frontend, backend, data, deployment)
Hands-on cloud experience with ownership of infrastructure
Experience with Google Cloud Platform (Cloud Run, Cloud SQL, Firebase)
Proficiency with AI-assisted coding tools (e.g. Cursor, Codex, Claude Code)
Strong system design and architectural judgment
Ability to work independently in ambiguous, fast-moving environments
Strong communication skills with both technical and non-technical stakeholders
Nice-to-Have
LLM engineering (RAG pipelines, evaluation, fine-tuning, agent frameworks)
Data engineering and applied machine learning
Python for scientific/numerical computing (NumPy, SciPy)
Experience in IoT, logistics, supply chain, or data-intensive systems
How to Apply
Submit your application with:
Updated resume
Current and Expected Salary
Notice period
Additional Information:
AWS plus Variably Bonus
A genuine learning budget: including the AI tools that make you faster (e.g. Claude Max plan)
The hardware you need to do your best work.
Ground-floor ownership of products with a real commercialization roadmap, and the chance to shape an engineering team from day one.