Data Engineer / AI Systems Engineer

Buchanan Technologies, Inc.; Dallas (TX); On-site; USD 90,000 - 120,000; Full time

Job summary

Buchanan Technologies, Inc. is seeking a skilled Data Engineer / AI Systems Engineer in Dallas, TX. This role focuses on building intelligent systems to enhance operational efficiency through data engineering and applied AI.

The ideal candidate will develop scalable ETL pipelines, integrate AI solutions, and work in a fast-paced environment. A Master’s degree in a relevant field along with strong experience in data engineering and SQL is preferred.

Qualifications

• 1–3 years of relevant professional experience preferred.
• Strong experience in data engineering and scalable ETL pipelines.
• Experience with building applications using LLMs.

Responsibilities

• Design, build, and maintain scalable ETL pipelines and data models.
• Develop and support data infrastructure using SQL and Azure Data Factory.
• Build AI-enabled applications using large language models.

Skills

Data engineering

SQL

Azure Data Factory

Building applications with LLMs

Data modeling

Automation workflows

Analytical skills

Problem-solving skills

Education

Master’s degree in Computer Science, Engineering, Data Science

Tools

Azure

Git

SQL Server

Python

APIs

Job description

Job Title

Location

Dallas, TX
Full-time | Direct Hire
Professional office environment with business-driven hours
Travel: Less than 10%, domestic only

Position Summary

We are seeking a highly skilled Data Engineer / AI Systems Engineer to join a dynamic, fast-paced technology team. This role sits at the intersection of data engineering, applied AI, and workflow automation, with a focus on building intelligent systems that improve decision-making and operational efficiency.

The ideal candidate will design and maintain scalable data infrastructure while also developing and deploying AI-driven solutions, including agentic workflows, retrieval-augmented generation pipelines, and automation tools built on top of existing large language models.

This role is critical in transforming how the organization leverages data and AI to streamline business processes across the enterprise.

Key Responsibilities

• Design, build, and maintain scalable ETL pipelines and data models.
• Develop and support data infrastructure using SQL, Python, Azure Data Factory, or similar tools.
• Build AI-enabled applications using large language models such as OpenAI, Anthropic, or similar APIs.
• Design and implement retrieval-augmented generation pipelines using embeddings and vector databases.
• Develop agentic AI workflows capable of multi-step reasoning, tool usage, and task automation.
• Build APIs, services, and backend systems to support data and AI-driven solutions.
• Work with business stakeholders to translate business needs into technical solutions.
• Support automation initiatives that improve operational efficiency.
• Ensure quality, scalability, performance, and reliability across data and AI systems.
• Manage multiple concurrent projects in a fast-paced environment.

Required Skills and Experience

• Strong experience in data engineering, including scalable ETL pipelines and data modeling.
• Advanced SQL skills, including performance tuning and working with large, complex datasets.
• Experience with Azure Data Factory or similar data integration tools.
• Hands-on experience building applications with LLMs such as OpenAI, Anthropic, or similar APIs.
• Experience designing and implementing RAG pipelines.
• Experience with embeddings and vector databases such as Pinecone, FAISS, Azure AI Search, or similar tools.
• Experience developing agentic AI workflows for automation and multi-step task execution.
• Familiarity with cloud platforms, preferably Azure; AWS or GCP experience is also acceptable.
• Experience with Git and modern software development practices.
• Strong analytical, problem-solving, and communication skills.
• Ability to work in a fast-paced environment and manage multiple priorities.
• Detail-oriented with a strong focus on quality and performance.

Preferred Skills

• Experience in fixed income, structured finance, or residential mortgage markets.
• Experience working with unstructured data pipelines.
• Experience with document parsing, OCR, and knowledge extraction.
• Familiarity with data pipeline orchestration tools such as Airflow.
• Experience with distributed data processing tools such as Spark.

Education

• Master’s degree in Computer Science, Engineering, Data Science, or a related field preferred.

Experience Level

• 1–3 years of relevant professional experience preferred.
• Candidates with strong project experience in data engineering, AI systems, LLM applications, or automation may also be considered.

Desired Competencies

• Accountability and ownership
• Strong drive for results
• Planning and organization
• Critical thinking and sound judgment
• Adaptability in changing environments
• Clear and proactive communication
• Ability to influence and build credibility