AI Engineer - Data Success

Citian•Washington, DC

4d•$125,000 - $175,000

About The Position

Citian is a venture-backed SaaS technology company developing software for transportation and infrastructure systems, including roads, rail, transit, bicycle, and pedestrian networks. The AI Engineer - Data Success supports the integration of AI into data extraction from client datasets and works with Engineering, Data, and Research teams to build scalable data-ingestion processes and improve data integrity. The role calls for resourcefulness, innovation, continuous process improvement, and effective communication and collaboration with cross-functional teams and stakeholders. The engineer evaluates AI outputs against real-world infrastructure standards, helps improve model performance and tool use, and supports computer vision strategies for infrastructure asset data extraction. The role also contributes to transportation- and infrastructure-specific model fine-tuning and evaluation, assesses third-party AI tools and models, and manages AI applications in QA/QC processes to improve data quality and integrity.

Requirements

Bachelor’s degree in Computer Science, Data Science, or a related field.
At least 3 years of professional experience in data-focused roles and at least 1 year of AI-focused experience, ideally in a product environment.
Understanding of Python and SQL code and the ability to retrieve and store data safely through a back end.
Familiarity with RESTful APIs and back-end concepts sufficient to prototype, test, and evaluate integrations.
Exposure to civil engineering, transportation infrastructure, or geospatial data sufficient to critically evaluate AI outputs in these domains and communicate credibly with domain experts.
Strong communication and collaboration skills for working with cross-functional teams and stakeholders.
Resourcefulness, innovation, and an ongoing focus on improving processes and efficiency.

Nice To Haves

Hands-on experience implementing RESTful API integrations.
Experience with cloud services, especially AWS, and using its features for scalable back-end AI solutions; S3 and Lambda Functions are mentioned.
Experience with computer vision or AI image-recognition applications, including at a prototyping or evaluation level.

Responsibilities

Evaluate whether AI outputs meet real-world infrastructure standards and coordinate with technical data teams.
Help improve model performance, including enabling models to use tools and applying other techniques to optimize LLM results.
Support AI image-recognition and computer-vision strategies for infrastructure asset data extraction by assessing model approaches, overseeing implementation, and validating outputs against domain benchmarks.
Collaborate with the research team on domain adaptation, benchmarking, model evaluation, and fine-tuning strategies for transportation- and infrastructure-specific models.
Evaluate and recommend third-party AI tools, APIs, and foundation models for Citian's use cases, balancing build-versus-buy tradeoffs with Engineering.
Own and manage the application of AI to QA/QC processes, direct strategy, evaluate outputs for domain accuracy, and iterate with the Data team to improve data quality and integrity.
Support scalable data ingestion and solutions to improve data integrity across client datasets.