AI Engineer

Cozi; Paris; Sur place; EUR 110 000 - 150 000; Plein temps

Résumé du poste

In Tandem is seeking an experienced AI Engineer to run and optimize our self-hosted AI inference stack and build product-facing AI features across OurFamilyWizard, Cozi, and FamilyWall.

You will own the infra on our GPUs, ensure performance and reliability, and collaborate with product teams to ship impactful AI capabilities for families.

Qualifications

• 5+ years shipping production software with meaningful AI/ML work.
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Responsabilités

• Run and optimize the self-hosted inference stack on dedicated multi-GPU hardware.
• Build and ship product-facing AI features and agents.
• Ensure latency, throughput and GPU utilization are optimized.

Connaissances

Python

Full-stack

AI/ML experience

Distributed systems

AWS

DevOps

Outils

vLLM

TensorRT-LLM

Claude Agent SDK

LangGraph

Docker

CI/CD

Description du poste

At In Tandem, we build technology that helps families manage everyday routines and navigate life’s biggest transitions. Through our four brands—OurFamilyWizard, Cozi, FamilyWall, and Custody Navigator—we help families stay organized, communicate well, and foster healthy childhoods.

We believe technology should strengthen relationships and make daily coordination less complicated. Everything we create is designed to lighten the mental load, reduce conflict, and support families through big and small moments.

If you want your work to make a real difference in the daily lives of parents and kids, In Tandem is the place where your impact will truly matter.

As our AI Engineer, you'll keep the AI infrastructure our products and teams run on fast, efficient, and reliable, and you'll build with it. You'll run and optimize our self-hosted inference stack on our own GPU hardware, build the internal platform our employees work through, and ship user-facing agents inside the apps. Your work spans OurFamilyWizard, Cozi, and FamilyWall, and the platforms that power how we build.

This is a hands-on technical role at its core: you own the technical side of running our models on our own hardware. But it's not siloed, and we don't want it to be. We're looking for someone who also wants to pick up app-layer work and ship product-facing features, and does both well.

Run and optimize our self-hosted inference stack

• Run the inference serving layer on our own GPU hardware: choose and tune the serving stack (vLLM, SGLang, TensorRT-LLM) for high throughput and low latency.
• Optimize aggressively: tensor parallelism, quantization (FP8, AWQ, GPTQ), KV-cache and prefix caching, continuous batching, speculative decoding, concurrency tuning.
• Serve multiple models and features off shared hardware: multi-LoRA, routing, and request scheduling that balances internal workloads against latency-sensitive product traffic.

Keep our AI fast, efficient, and observable

• Make our AI workloads efficient: improve latency, throughput, and GPU utilization so we get the most out of what we run.
• Build the visibility: instrument performance and usage across our AI surfaces so there's clear data on how everything is running.
• Surface the technical tradeoffs (performance, latency, efficiency) so the people making the calls have what they need to make them.

Build AI features and proactive agents

• Ship the in-app agent layer that helps families coordinate: proactive nudges, smart suggestions, agents that summarize, draft, schedule, and act for busy parents.
• Build the substrate underneath: tools, memory, orchestration, guardrails, and evaluation harnesses, integrated cleanly with production APIs alongside our architecture team.
• Work in nimble pairs with feature owners, standing up whatever's needed to test an idea, including a vibe-coded UI when that's the fastest path to a real customer. Ship rough, learn fast, harden what works.
• Technical and hands-on with infrastructure: you like running real systems on real hardware and keeping them fast and reliable.
• A full-stack builder who wants the app layer too: you don't want to be boxed into infra. When a feature needs shipping, you want to pick it up and ship it, not just hand it off.
• Performance-minded: you treat latency, throughput, and efficiency as things to engineer deliberately.
• Rapid-prototyping and AI-first, with modern tooling (Claude Code, agent SDKs) part of your craft.
• Motivated by work that matters. Families rely on these products during real moments in their lives.
• 5+ years shipping production software, including meaningful applied AI or ML work.
• Demonstrated experience running and optimizing self-hosted LLMs on dedicated multi-GPU hardware: a serving stack (vLLM, SGLang, or TensorRT-LLM) and the optimization that comes with it (tensor parallelism, quantization, batching, KV cache).
• A track record of optimizing inference performance and efficiency (latency, throughput, GPU utilization).
• Strong Python and engineering fundamentals, with the full-stack range to stand up a quick UI, and the genuine desire to work app-layer features and not only infra.
• Hands‑on with agent frameworks (Claude Agent SDK, LangGraph, or similar), LLM APIs, embeddings, and RAG.
• Comfortable with AWS and the devops this role owns: Docker, CI/CD, monitoring, and observability.
• Experience building internal tooling or platforms others depend on. Bonus for Slack apps, MCP, or agent orchestration at team scale.

Why Join?

We’re redefining family technology. In Tandem brings together a growing portfolio of trusted tools that support families, and the professionals who guide them, through the moments that matter most. We bring clarity to chaos and stability to daily family life, helping parents feel less stressed so kids can have healthier childhoods.

Scale meets startup energy. With more than 20 years of impact and a strong market presence, we’re entering a bold new chapter of growth. We have the foundation, the momentum, and the ambition to go further: expanding our reach, deepening our impact, and elevating the tools families and professionals rely on every day.

Purpose-driven. Performance-focused. People‑first. Our culture is rooted in accountability, curiosity, and collaboration. We value diverse perspectives, thoughtful problem‑solving, and teammates who care deeply about building something that matters.