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Backend Engineer - AI Agent & Governance

SuperblocksSuperblocks·Software Development

Compensation

$90,000 - $120,000/year

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Posted

300 days

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About the role

Superblocks is reimagining software development for a billion builders. Our mission is to help every team build, deploy, and manage AI-powered software with full control and flexibility.

Why Join Us?

We’re one of the fastest-growing AI startups, backed by top-tier investors and widely adopted by companies like Instacart, Sofi, Betterment, and Carrier. Our team comes from Uber, Stripe, Datadog, Confluent, Elastic, and Google, and has founded/architected systems like Kafka, Kibana, Debezium, Datadog APM, and more.

Since launching Clark, our AI builder, the response has been overwhelming with strong adoption from enterprises across different industries.

We’re fully in-person at our NYC HQ near Union Square and are looking for exceptional engineers who are passionate about creating great products.

The Role

You’ll play a key role in designing and developing the core systems that build and manage hundreds of thousands of AI applications. You’ll thrive here if you’re low-ego, hands-on, and energized by building fast, learning constantly, and solving real-world problems with smart teammates.

Responsibilities:

  • Design and develop the core control plane for AI agents that supports custom RBAC, auth, AI guardrails, auditing and observability.
  • Develop systems that support multiple tenants and run across cloud and on-prem setups.
  • Build, deploy, and optimize AI agent performance, alignment and evals.
  • Work closely with customers to ship high-impact features driven by real-world use.
  • Partner with product to define the roadmap and bring new AI tooling to life.

Must haves:

  • 3+ years of experience in full-stack or backend engineering with expertise in scalable system design and architecture
  • Strong product sense focused on great user experiences and strategic thinking to meet market and customer needs.
  • You’re all-in and committed to building a generational AI company, far beyond a 9 to 5 job.

Nice to haves:

  • Built and operated production AI systems and are familiar with AI inference techniques.
  • Optimized language runtimes and enable cross-language integration (e.g., Go, Python, C), including customizing or building WASM compilers and runtimes.
  • Experience with machine learning algorithms, platforms, and frameworks like PyTorch and Tensorflow.

Compensation

The base salary ranges between $175,000–$225,000+ USD, plus a generous equity package. Final comp will be based on experience and skills.

If you’re excited to build the experience that can enable the next billion builders and AI-powered apps, let’s talk.

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Aplyr's read

Superblocks is a cutting-edge platform enhancing developer productivity, attracting tech-savvy professionals focused on software efficiency and innovation.

Synthesized from recent postings & public sources

What's promising

  • Superblocks offers a platform that significantly boosts developer productivity, appealing to efficiency-driven professionals.
  • The company is expanding rapidly, hiring diverse roles from engineers to account executives.
  • Focus on AI and enterprise platforms presents growth opportunities in emerging tech sectors.

What to watch

  • Highly competitive tech industry may challenge Superblocks' market position.
  • Rapid expansion could strain internal resources and company culture.
  • Limited public information about financial stability and long-term sustainability.

Why Superblocks

  • Superblocks specializes in simplifying complex software deployment processes.
  • Emphasis on AI integration differentiates it from traditional software platforms.
  • The platform's focus on operational efficiency appeals to productivity-centric developers.

Aplyr’s read is generated by AI from public sources. Was it useful?

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About Superblocks

Superblocks is a platform that simplifies the development and deployment of software applications, focusing on enhancing developer productivity and operational efficiency.

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