Member of Technical Staff, Platform

Embedding Vc
United States
Hybrid

Who this role is best for

A natural match if you have experience building full-stack product features in a fast-growing AI company.

Best fit for

  • Candidates with full-stack engineering experience and a product mindset who can drive AI integration into workflows
    — “you need to have full-stack (FE and BE) fluency and a product mindset
  • Individuals with AI-native habits and experience deploying LLM-powered features in production
    — “AI-native by default: you already use AI coding tools daily, and you've built or shipped features that use LLMs/AI

Things to consider

  • The role demands end-to-end ownership of features, which may require significant autonomy and decision-making
    — “Own features end-to-end, from product discussion through implementation, testing, and release
  • The position may require adapting to shifting priorities as the platform scales rapidly
    — “the product is growing and scaling significantly in the 1-100 stage

How to stand out

  • Highlight AI-powered feature work and cross-functional collaboration in your resume and interview stories
    — “Embed AI directly into product workflows: AI-powered features, assistive UX, and automation
  • Emphasize your ability to ship features quickly and iterate based on user feedback
    — “Design, build, and ship full-stack product features — UI, API, and data layer — with a strong bias toward shipping and iterating quickly
  • Showcase your fluency in both frontend and backend technologies, particularly React/TypeScript and distributed systems
    — “Comfortable working across the stack, including modern frontend frameworks (e.g. React/TypeScript) when the product needs it
  • Demonstrate your experience with building evaluation pipelines and data models for AI features
    — “Build evaluation pipelines and data models for AI-powered features
  • Position yourself as a leader who shapes product scope and UX, not just follows specs
    — “Partner closely with Product and Design to shape scope and UX, not just implement a spec handed to you
Pace · SteadyCollaboration · HighAutonomy · MediumDecision Impact · TeamLevel · Junior

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • designs, builds, and ships full-stack product features
  • owns features end-to-end
  • embeds AI directly into product workflows
  • builds evaluation pipelines and data models for AI-powered features
  • partners closely with Product and Design
Typical background
1+ years of professional software engineering experiencestrong backend fundamentalscomfortable working across the stack

Skills & requirements

Required

ReactTypeScriptAPI DesignData ModelingDistributed SystemsRelational DatabasesLlm-powered FeaturesAI Coding ToolsProduct MindsetAi-native ApproachSolid Engineering FundamentalsComfortable With Ambiguity

Preferred

Startup ExperienceFounder Experience

Stack & domain

ReactTypeScriptAPI DesignData ModelingDistributed SystemsRelational DatabasesLlm-powered FeaturesAI AgentsLlms/aiProduct MindsetOwnershipPragmatismBias Toward ShippingAIData PipelinesCloud Platforms

About the role

Original posting from Embedding Vc via Ashby

About Abaka

Abaka AI is built on one mission: to be the world's most trusted data partner for AI companies. More than 1,000 industry leaders across Generative AI, Embodied AI, and Automotive AI rely on us to power their data pipelines. With our headquarters in Silicon Valley—and teams in Paris, Singapore, and Tokyo—we support global partners with fast, reliable, and scalable data solutions.

Our offerings include a diverse catalog of off-the-shelf datasets (image, video, multimodal, reasoning, 3D, and beyond) as well as comprehensive data collection and annotation services. Whether teams need raw data, curated datasets, or full-cycle data engineering, Abaka AI provides the foundation for building high-performance AI systems.

About the Role

As a Member of Technical Staff, Platform, you'll build full-stack product features for our Expert Talent platform end-to-end—from a rough idea in a product discussion to a shipped, instrumented feature in front of real customers and users. You'll work across the stack (frontend, backend, and the glue between them) and work closely with cross-functional teams like product, project management, and leadership.

This is a generalist product engineering role, and you need to have full-stack (FE and BE) fluency and a product mindset in the way you approach development. You care as much about whether a feature solves the customer and users' problems as you do about how it's built. Our Expert Talent platform is growing and scaling significantly in the 1-100 stage, so your impact will be immense and have a great deal of ownership from day one.

Responsibilities

  • Design, build, and ship full-stack product features — UI, API, and data layer — with a strong bias toward shipping and iterating quickly.
  • Own features end-to-end, from product discussion through implementation, testing, and release.
  • Embed AI directly into product workflows: AI-powered features, assistive UX, and automation that make the product feel intelligent, not just functional.
  • Build evaluation pipelines and data models for AI-powered features.
  • Leverage modern AI coding tools to accelerate development while maintaining a high engineering bar.
  • Partner closely with Product and Design to shape scope and UX, not just implement a spec handed to you.
  • Improve the performance, reliability, and observability of assessment infrastructure.

Qualifications

  • 1+ years of professional software engineering experience building and shipping production features.
  • Strong backend fundamentals: API design, data modeling, distributed systems, and relational databases.
  • Comfortable working across the stack, including modern frontend frameworks (e.g. React/TypeScript) when the product needs it.
  • Experience building or integrating LLM-powered features in production is a strong plus.
  • Knowledge of building AI agents into products.
  • Product-minded: you ask "why should we build this" and "is this the right solution" as naturally as "how do I build this," and you treat customer outcomes as the measure of success, not the technology you shipped.
  • AI-native by default: you already use AI coding tools daily, and you've built or shipped features that use LLMs/AI.
  • Solid engineering fundamentals: testing, debugging, performance basics, and the judgment to know when to invest in each.
  • Comfortable with ambiguity and evolving priorities.
  • High ownership, pragmatism, and a bias toward shipping.

Preferred Qualifications

  • Startup or founder experience.
  • Experience building consumer-facing products at scale.
  • ML and Deep Learning knowledge and experience.
  • Experience with microservices, event-driven architectures, and cloud platforms (AWS/GCP).

Compensation & Benefits

The base salary range for this position is $120,000 – $200,000 USD annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work at Abaka AI. This role is eligible for equity, as well as a comprehensive benefits package (health, dental, vision, PTO, flexible work schedule).

Source: Embedding Vc careers (Ashby)

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