AI Engineer

In Tandem

$100K — $135K *
US-AnywhereRemote in United States
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of production software experience, including applied AI or ML work.
  • Experience with self-hosted LLMs on multi-GPU hardware and relevant optimization techniques.
  • Track record of optimizing inference performance, including latency and throughput.
  • Proficiency in Python and full-stack development for UI and app-layer features.
  • Hands-on experience with agent frameworks and LLM APIs.
  • Familiarity with AWS, Docker, CI/CD, and observability tools.
  • Experience in building internal tools that others rely on.

Responsibilities

  • Run and optimize self-hosted inference stack on GPU hardware.
  • Improve AI workloads for efficiency in latency and throughput.
  • Build visibility tools for AI performance and usage data.
  • Develop in-app agents that assist families with organization.
  • Create underlying infrastructure for AI features and tools.
  • Collaborate closely with feature owners to prototype and ship solutions.
  • Balance the demands of multi-model serving while ensuring low latency.

Benefits

  • 100% medical premium covered for employees and 99% for family members.
  • 401k plan with up to a 4% match and immediate vesting.
  • Paid leave for new parents and generous PTO policies.
  • Learning and development stipend provided for employees.
  • Supportive work environment with flexible remote work options.
Full Job Description
AI Engineer

Department: Data Engineering

Employment Type: Permanent - Full Time

Location: Remote USA - In Tandem

Compensation: $100,000 - $135,000 / year

Description

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.

What you will accomplish:

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.


Who you are:
  • 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.


What you bring:
  • 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.

How we support you:
  • 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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