Hire Hangar

media

Full-StackAIEngineer

$3–4k San Francisco, California, United States; New York, New York, United States CONTRACT Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Full-Stack AI Engineer at Hire Hangar. Skills: Full-Stack AI Engineering, Data Ingestion Pipelines, AI Agent Development, React Frontend. Build data ingestion and intelligence layer. Architect and ship data transformation pipelines”

What You'll Achieve.

Ship pipelines that transform data; Expose data through AI agents and frontend; Meet enterprise-grade requirements; Serve AI agent tools with accurate, low-latency responses; Surface actionable optimisation insights

Industry & Context.

media
Problems you'll solve

Reasoning across cloud services; Bridging edge compute and managed services; Multi-step reasoning workflows

Eligibility Requirements

Must have prior remote work experience, Fluent with remote collaboration tools and platforms, Ideally worked with US or UK-based companies, Record a video as part of application process

What They're Looking For.

Must Have

TypeScript, Production experience with serverless or edge runtimes, Demonstrated experience building durable, idempotent ingestion pipelines, Practical, production-level understanding of embeddings, chunking strategies, and retrieval quality tuning, At least one agent-style system shipped to production, React fluency with modern patterns and component architecture, Comfort operating across two cloud, Prior remote work experience, Fluent with remote collaboration tools and platforms

Nice to Have

Experience building or operating RAG systems in production, Familiarity with current embedding models and the tradeoffs across dimension, quality, and cost, Background in ETL design, observability for data pipelines, or evaluation frameworks for retrieval quality, Adtech, performance marketing, or marketing analytics background, Opinions on vector databases backed by hands-on experience

What You'll Do.

Build data ingestion and intelligence layer

Architect and ship data transformation pipelines

Expose data through AI agents and React frontend

Design and build ingestion pipelines

Generate and manage embeddings

Build and maintain retrieval pipelines

Ship agent-style systems

Develop and maintain React frontend

Own full system lifecycle

Contribute to stack decisions

Collaborate with product and enterprise partners

How You'll Work.

Team & Collaboration

Collaborate closely with product and enterprise partners

Full Job Description

Join Hire Hangar and work with fast-growing global companies while building a long-term, remote career. Job Title Full-Stack AI Engineer – Platform Team (AI Intelligence Layer) Location Remote Time Zone US Time Zones (EST–PST) Role Overview We are seeking a senior Full-Stack AI Engineer to join our platform team and own the end-to-end build of a data ingestion and intelligence layer for enterprise customers in the media vertical. This is a high-impact, high-ownership role at the intersection of AI, data engineering, and product. You will architect and ship pipelines that transform unstructured creative assets and ad performance data into a semantic, vector-based layer — and expose it through AI agents and a polished React frontend. We move fast, ship to production, and hold a high bar for craft and reliability. What You'll Build - A dual-mode data ingestion engine handling creative components (CTAs, headers, body copy, images, video, and metadata) and ad performance data (channel-level signals tied to those components) - Multi-modal embedding generation and storage — vector plus structured — optimised for retrieval quality and cost - AI agent tooling that enables natural language search, comparison, and reasoning across the creative and performance data layer - A React frontend that lets users explore the creative library, query performance data in plain English, and surface actionable optimisation insights - Audit-logged decisioning and governance infrastructure to meet enterprise-grade requirements Key Responsibilities - Design and build durable, idempotent ingestion pipelines for creative and performance data at scale (queues, retries, backpressure, dedup, schema evolution) - Generate and manage embeddings for multi-modal creative assets; select and operate the right vector store for the workload - Build and maintain retrieval pipelines that serve AI agent tools with accurate, low-latency responses - Ship agent-style systems with tool use, state management, and m

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