Member of Technical Staff, Platform
Summary
Build full-stack features for Abaka’s Expert Talent platform, integrating AI-powered workflows and evaluation pipelines while owning features from design to release.
-
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.
-
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 in building AI Agents into productinos
-
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.
-
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).