Meitner Energy is developing advanced nuclear energy solutions intended to deliver reliable, scalable, and carbon-free electricity for industrial and grid applications.

Our international team brings together nuclear, engineering, commercial, regulatory, and project-development experience. We are building an organization focused on disciplined engineering, responsible execution, and the deployment of nuclear energy at meaningful scale.

The Opportunity

Meitner’s AI platform is being built now, and this role owns it end to end. You will design and deliver the model-serving infrastructure, the gateway and router layer, the retrieval pipeline, and the tiered hosting architecture that allows engineers, operators, and commercial teams to use AI safely on export-controlled and otherwise sensitive technical material. You will also personally deploy and tune the serving lanes, own the pipelines and automated tests that keep the platform reliable, and run the evaluation process that determines which models reach production. Alongside that mandate, you will act as the company’s corporate cloud and infrastructure architect, owning the public cloud footprint and the design decisions that shape where workloads and data live.

The role carries genuine engineering authority. You will set code-quality, review, testing, and release standards for the platform, serve as the primary technical interface to security, compliance, and export-control stakeholders, and lead model evaluation and selection across a fast-moving landscape of open-weight and proprietary models. The work touches Meitner’s reactor program directly, and routing sensitive material to the right place is a requirement rather than an aspiration.

This role is adecuado for someone who:





- Wants to design and build a production LLM platform rather than operate one that is already finished.
- Takes real ownership of reliability: writes tests, enforces gates, and does not ship work they are not confident in.
- Is fluent across the modern platform stack, including Python, containers, container orchestration, and high-throughput model serving, and can move quickly without cutting corners.
- Finds the intersection of high-performance inference and security-conscious regulated environments interesting rather than frustrating.
- Communicates architecture and engineering decisions clearly to executive, regulatory, and cross-site audiences without losing precision.

What You’ll Do

AI Platform Architecture and Delivery

Design and own the end-to-end architecture of Meitner’s private AI platform, including the model-serving stack, the gateway and router layer, and the retrieval pipeline. Architect and enforce the tiered hosting design that separates regulated workloads from general-purpose workloads, and ensure the resulting controls satisfy the export-control and controlled-information requirements that apply to advanced nuclear technology. Lead model selection and sequencing across candidate open-weight and proprietary models, own the evaluation harness used to make those decisions, and design GPU infrastructure sized to serve those models reliably, with a capacity plan tied to program milestones.





Model Serving and Inference

Deploy, configure, and tune high-throughput model-serving infrastructure, managing quantization strategy and GPU memory planning so that target models fit the available hardware within budget. Monitor inference latency, throughput, and utilization, identify and resolve bottlenecks across the serving stack, and support capacity planning and infrastructure sizing decisions.

Gateway, Routing, and Platform Reliability

Implement and maintain the gateway and router rules that govern access to the platform, including token accounting, prompt-injection defenses, model version pinning, and request routing between regulated and non-regulated serving tiers. Manage controlled model promotion and rollback so that platform state remains auditable and reversible, and contribute to the platform’s security posture by supporting data-sensitivity routing and export-control requirements in the design of every change you make.

Continuous Delivery, Testing, and Engineering Standards

Own the continuous integration and delivery pipelines for platform code, and establish the automated test coverage and quality gates that enforce the platform’s engineering standards. Set and enforce the code-quality, code-review, testing-gate, and release-governance standards under which the platform is built, establish deployment and rollback practices that meet the reliability and auditability expectations of a nuclear engineering environment, and raise the engineering bar through hands‑on review, pairing, and documented standards that others can follow without you in the room.

Run structured comparisons across candidate open-weight and proprietary models usin

📌 AI Platform Engineer (Buenos Aires)
🏢 Meitner Energy
📍 Buenos Aires