Senior Backend AI Engineer

About the role

You will architect the next generation of data intelligence by designing backend systems that use artificial intelligence to interpret and restructure complex information flows. This role owns the core logic that allows our platform to transform raw, unstructured data into actionable insights without relying on rigid, manual pipelines. You will build self-healing mechanisms that detect anomalies, diagnose failures, and automatically adjust processing logic to maintain continuity. Your work will directly shape how our infrastructure leverages large language models and AI agents to make data processing decisions. You will lead the implementation of intelligent connectors that interact with diverse sources and adapt to their changing schemas autonomously. You will mentor engineers on writing robust tests and implementing observability strategies tailored for AI-augmented applications. In this capacity, you will act as a key technical leader responsible for ensuring the reliability and intelligence of our data infrastructure. Your contributions will define the boundary between traditional data engineering and adaptive, cognitive processing systems.

Key facts

What you'll do

Architect autonomous data processing engines that utilize AI to dynamically parse, map, and transform unstructured content across heterogeneous environments.

Design and implement self-healing pipeline logic capable of diagnosing upstream disruptions, adjusting to schema evolution, and validating data integrity in real time.

Spearhead the optimization of high-velocity analytics workloads by architecting low-latency ingestion paths into ClickHouse and BigQuery to support OLAP efficiency.

Lead the scaling of intelligent connectors that leverage AI models to ingest and normalize data from non-standardized APIs, streaming sources, and object storage at massive scale.

Drive the establishment of AI-assisted testing frameworks and observability protocols to ensure backend stability and performance in production deployments.

Collaborate closely with data science teams to integrate machine learning models and large language models directly into backend services and data transformation workflows.

Define and enforce architectural best practices that balance the flexibility of AI-driven logic with the reliability required for enterprise-grade data platforms.

Champion the ownership of the data platform's "brain," ensuring that the system adapts to shifting business requirements and environmental changes autonomously.

Guide the team in adopting modern engineering practices that merge traditional backend stability with cutting-edge AI capabilities for data processing.

Influence product direction by translating complex technical constraints and opportunities into clear strategies for enhancing the intelligence of the global data infrastructure.

Requirements

You hold a Bachelor's degree in Computer Science, Software Engineering, or a closely related technical field as a non-negotiable baseline for this position.

You bring a minimum of 5 years of professional experience in backend engineering, with a proven track record of delivering scalable, high-performance systems.

You possess deep mastery of Python, including the ability to write production-grade code that interfaces with complex AI models and data libraries.

You have direct experience integrating LLMs or advanced AI models into backend services or data-intensive workflows to solve real business problems.

You are a power user of OLAP databases such as ClickHouse, BigQuery, or Snowflake, with expertise in schema design, indexing, and materialized views.

You demonstrate a strong background in distributed systems, including experience with cloud platforms like AWS or GCP and streaming technologies such as Kafka, Flink, or Spark.

You have a proven adaptive mindset, building systems that are designed to anticipate changes in the environment and recover from failures without human intervention.

You have a history of product ownership, leading high-impact initiatives and taking responsibility for the strategic direction of critical platform components.

You are comfortable working in a fast-paced environment where requirements evolve, and you must balance innovation with the need for robust, maintainable code.

You communicate effectively with both technical and non-technical stakeholders, translating complex concepts into actionable plans for cross-functional teams.

Nice to have

Experience with building data platforms that handle streaming ingestion and real-time analytics at scale.

Familiarity with containerization and orchestration tools such as Kubernetes to manage backend services and AI workloads.

Knowledge of data governance, security best practices, and compliance standards relevant to handling large datasets.

Exposure to MLOps practices and the deployment lifecycle of machine learning models in production environments.

Practical notes

This is a full-time position based in Cleveland, Ohio.

Candidates must be eligible to work in the United States without sponsorship at this time.