Data & AI Infrastructure Engineer

About Us

Role Overview

What You'Ll Actually Be Doing

• Design and build the ingestion pipelines for live market data sources across multiple regions pricing indices, transaction feeds, rental yield benchmarks — each market bringing its own provider, schema, and data format
• Architect our PostgreSQL + pgvector data warehouse to scale cleanly from 1 to 50+ markets, each with different schemas, currencies, and data freshness requirements
• Build the API integration layer connecting Alpha to a growing list of external data providers, internal tools, and third-party services — designing for reliability, not just "it works once"
• Transform raw market data into structured chunks ready for RAG retrieval — partnering directly with our AI engineer to ensure what gets embedded is actually useful, accurate, and current
• Build monitoring and alerting for data pipeline health — freshness, completeness, schema drift so AI failures caused by bad data get caught before they reach a user
• Own infrastructure decisions around scaling — when to introduce caching, queuing (Celery/Redis), or a proper ETL framework as data volume grows
• Work as a technical peer to our AI engineer — you own the data and infrastructure layer, they own the AI/retrieval layer, and you build the connective architecture together

What We'Re Looking For

• Strong experience designing and operating production data pipelines — not just SQL queries, but the architecture of ingestion, transformation, and storage at scale
• Hands-on experience with PostgreSQL and ideally pgvector, or comparable vector-capable data stores
• Real experience integrating multiple third-party APIs reliably — handling rate limits, auth, retries, and data quality validation
• Comfort with Python for pipeline development; familiarity with task queues (Celery, Redis) or workflow orchestration tools is a strong plus
• Understanding of how AI/RAG systems consume data — you don't need to build the models, but you need to understand what "good input" looks like for retrieval and embedding
• Experience designing for multi-region or multi-currency systems is a strong plus, given our international franchise roadmap
• Comfort working in a fast-moving startup environment — you'll be making real architecture decisions early, not following someone else's spec

What We Offer

• Full ownership of the data and infrastructure layer for a live AI product already in production your architecture decisions shape what's possible for the entire platform
• Direct partnership with our AI engineering lead — two senior technical hires building the brain of the company together
• Work alongside a small, senior team with direct access to leadership and fast decision-making no layers of bureaucracy between your idea and shipping it
• Competitive compensation with meaningful growth as the platform and team scale internationally