AI Engineer

🕒 Junho 16

🗣️🇺🇸🇬🇧 Inglês obrigatório

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In Tandem

51 - 200 funcionários

👥 B2C

☁️ SaaS

⚡ Produtividade

B2C • SaaS • Productivity

In Tandem é uma plataforma global de tecnologia que desenvolve ferramentas digitais e aplicativos para apoiar famílias em etapas importantes e no dia a dia. A empresa cria e opera soluções focadas no consumidor, incluindo aplicativos de coparentalidade, organização familiar, comunicação e agenda parental, que visam melhorar a conexão, a coordenação e a tranquilidade para famílias modernas. Os produtos da In Tandem são projetados para simplificar rotinas, apoiar a coparentalidade e a comunicação familiar, além de fornecer recursos em momentos desafiadores.

Descrição

• 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.

🎯 Requisitos

• 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.

🏖️ Benefícios

• Medical: In Tandem pays 100% of the premium for employees AND 99% for all additional family members • 401k: Up to a 4% match with immediate vesting • Paid leave for all new parents • Learning & Development stipend for employees • Paid Time Off: 11 Holidays + Winter Break (3 Days) + Volunteer Time Off (1 Day) + Floating Holiday (1 Day) • Personal Time Off: 15 days for 0-1 years of employment, 20 days 1-3 years of employment • Supportive and flexible working environment – work from anywhere!

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