Senior AI Infrastructure Engineer

Ferry International; Dallas (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

Ferry International is seeking a Sr. Data Platform Engineer to own and build the data pipelines, embedding retrieval, and AWS infrastructure powering our AI applications.

You will maintain production-grade systems, enable scalable data processing, and ensure secure, observable operations across the stack. You’ll work across data engineering, cloud infrastructure, DevOps, and AI systems, turning validated ideas into reliable products while maintaining high performance and cost effectiveness.

Qualifications

• 5 to 8 years of relevant engineering, data engineering, or related experience.
• Strong Python and SQL skills with hands-on 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.

Responsibilities

• 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 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 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 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.
• 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.
• 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.

Skills

Python

SQL

PostgreSQL

Vector databases

AWS

Containers

CI/CD

Infrastructure as Code

Embeddings

Retrieval systems

LangGraph / LangChain

Observability

Reliability / Security / Cost

Communication & Collaboration

Job description

Ferry International is seeking a Sr. Data Platform Engineer to own and build the data pipelines, embedding retrieval, and AWS infrastructure powering our AI applications.

You will maintain production-grade systems, enable scalable data processing, and ensure secure, observable operations across the stack. You’ll work across data engineering, cloud infrastructure, DevOps, and AI systems, turning validated ideas into reliable products while maintaining high performance and cost effectiveness.