Sr. AI Platform Engineer

Ferry International; Meridian (ID); On-site; USD 140,000 - 200,000; Full time

Job summary

Ferry International seeks a Sr. Data Platform Engineer to own the data foundation and platform surrounding our AI applications. You’ll build data pipelines, retrieval systems, AWS infrastructure, and memory/evaluation systems to improve AI products in production.

You’ll lead end-to-end ownership—from ingestion and processing to deployment, monitoring, and cost awareness—while ensuring reliability, security, and scalable performance for next-generation coaching technology.

Qualifications

• 5 to 8 years of relevant engineering, data engineering, infrastructure, or related experience.

Responsibilities

• Build production-ready data and ML pipelines transforming validated modeling into reliable systems.
• Own ingestion, cleaning, embeddings, scoring, and processing of coaching transcript data.
• Modernize embedding infrastructure and consolidate vector storage for performance and reliability.
• Own the data corpus and retrieval layer end-to-end.

Skills

Python

SQL

Data pipelines

Tools

PostgreSQL

pgvector

AWS (ECS, Fargate, RDS, S3)

Job description

Who We Are

Ferry International is the #1 real estate coaching company in the world. We help real estate professionals build stronger businesses, create better lives, and achieve measurable results through coaching, training, technology, and community.

We are also building what comes next.

As AI becomes an increasingly important part of how we serve our clients, we are investing in the infrastructure, data, and technology required to turn promising ideas into reliable products. This is an opportunity to join a team that is building that foundation from the ground up.

THE ROLE

We’re looking for a Sr. Data Platform Engineer to own the systems underneath and around our AI applications.

Our engineering lead owns discovery and agent design. They focus on the business questions, modeling, and orchestration logic. You’ll own everything that makes those systems dependable in production.

You’ll build the data pipelines that feed our AI, the retrieval systems that help it access the right information, the AWS infrastructure it runs on, and the memory and evaluation systems that allow it to improve over time.

This is a hands on builder role for someone who enjoys taking validated ideas and turning them into reliable, scalable production systems. You’ll have significant ownership and the opportunity to shape the technical foundation behind our next generation of AI products.

WHAT YOU’LL DOBuild The Data Foundation

• Build and maintain production ready data and machine learning pipelines that transform validated modeling into reliable systems.


• Own ingestion, cleaning, embeddings, scoring, and processing across our coaching transcript data.


• Solve the real world data problems that come with a growing system, including mixed storage formats, missing records, historical data, and backfill requirements.


• Own the data corpus and retrieval layer from end to end.


• Modernize embedding infrastructure and consolidate vector storage to improve performance and reliability.


• Ensure retrieval is properly scoped and isolated for each client.

Own the Platform

• Own how our AI systems are deployed, operated, monitored, and scaled.


• Build and maintain containerized deployments, CI/CD pipelines, infrastructure as code, environments, observability, alerting, and cost monitoring across AWS.


• Create infrastructure that is reliable, secure, scalable, and cost effective.


• Build the dashboards and monitoring systems that allow the team to understand system performance and identify issues before they become problems.

Build AI Memory & Infrastructure

• Build the durable state, client memory, and retrieval layers that support our AI agent applications.


• Create systems that allow client profiles, commitments, history, and other important information to persist across interactions and over time.


• Make those systems fast, reliable, observable, and scalable.


• You won’t own the overall agent design. You’ll own the infrastructure that makes the agent work consistently in production.

Build the Evaluation System

• Turn established evaluation criteria and benchmark data into automated systems that measure AI performance at scale.


• Build automated evaluations that can run through CI and help determine whether new releases are ready for production.


• Develop regression testing and monitoring processes that help the team identify performance issues and maintain quality as the system evolves.

Protect the Data

• Treat client and conversation data as sensitive information.


• Build and maintain appropriate systems for retention, access control, encryption, and data security.


• Develop a clean and reliable process for removing client information when requested.


• Help ensure our AI infrastructure is built with security, privacy, and responsible data management in mind.

Who You Are

• You’re a builder.


• You enjoy taking something that works in a development environment and figuring out how to make it reliable in production.


• You’re comfortable working across data engineering, cloud infrastructure, DevOps, and AI systems.


• You don’t need everything perfectly defined before you start. You can work through ambiguity, identify what needs to be built, and create practical solutions.


• You care about reliability and performance, but you also understand that technology needs to support real business and customer outcomes.


• You’re comfortable working independently, but you know when to collaborate, ask questions, and bring others into a decision.


• Most importantly, you enjoy solving difficult technical problems and building the infrastructure that allows ambitious ideas to become real products.

Requirements

• 5 to 8 years of relevant engineering, data engineering, infrastructure, or related experience.


• Strong Python and SQL skills with hands on experience building data pipelines using PostgreSQL.


• Experience with vector databases or vector search technologies such as pgvector.


• Strong AWS experience, including services such as ECS, Fargate, RDS, and S3.


• Experience with containers, CI/CD, infrastructure as code, and cloud operations.


• Experience building data infrastructure supporting machine learning or LLM applications.


• Hands on experience with embeddings and retrieval systems.


• Working familiarity with LangGraph or the LangChain ecosystem.


• Experience building observability, monitoring, dashboards, and alerting for production systems.


• Strong understanding of system reliability, scalability, security, and cost management.


• Ability to take validated modeling and transform it into production grade systems.


• Strong communication and collaboration skills.

NICE TO HAVE

• Experience with Model Context Protocol (MCP) or similar tool calling interfaces.


• Experience with LLM evaluation and observability tools, including LLM as judge systems, tracing, and regression suites.


• Experience with TypeScript and React for internal dashboards or administrative tools.


• Experience working with AI products or agent based applications.

PERKS & CULTURE

You’ll be joining a fast moving, high accountability team that values ownership, collaboration, and building things that matter.

At Ferry International, we live by four values:

Collaborate

We’re stronger as a team than we are as individual stars.

Serve

We put our clients and each other first.

Grow

We expect a growth mindset in ourselves, our careers, and the business.

Take Ownership

See it through. Finish line and all.

This is an environment where good ideas can come from anywhere, technical challenges are encouraged, and you’ll have the opportunity to make a meaningful impact on the systems behind our next generation of products.

If you’re excited about building the infrastructure that turns AI from an idea into a dependable product, we want to meet you.

Ferry International is an Equal Opportunity Employer.