AI Engineer
Job Description
Onsite in Dallas, TX, this entry-level AI Engineer role centers on hands-on development of Generative AI solutions within a regulated financial services environment. You will build real-world AI applications and workflows while learning enterprise-grade practices.
You will collaborate with cross-functional teams, contribute to data ingestion and retrieval pipelines, and grow your skills in responsible AI, security, and compliance as you work through practical AI projects from concept to execution.
Responsibilities
- Assist in building and enhancing Generative AI applications such as RAG-based solutions, internal copilots, and AI-powered workflows.
- Contribute to prompt development, testing, and basic evaluation of LLM outputs.
- Support implementation of data ingestion, chunking, embeddings, and retrieval pipelines.
- Write and maintain clean, well-tested code using Python.
- Work with cloud-native services (Azure and/or AWS).
- Participate in CI/CD pipelines and automated testing.
- Learn and follow Responsible AI, security, and compliance guidelines.
- Collaborate with cross-functional teams to understand business use cases.
- Document implementations and contribute to knowledge sharing.
- Stay current with emerging GenAI tools and practices.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, AI/ML, or a related field.
- 0–5 years of experience in software development, data engineering, or AI/ML (internships count).
- Foundational understanding of AI and machine learning concepts.
- Exposure to Generative AI concepts such as LLMs, embeddings, or retrieval-based systems.
- Hands-on experience with Python.
- Familiarity with cloud concepts (Azure or AWS).
- Knowledge of Git and software development workflows.
- Strong problem-solving skills and eagerness to learn.
- Good communication and teamwork skills.
Technologies
- Python
- Azure
- AWS
- Git
- Azure OpenAI
- OpenAI APIs
- Hugging Face
- LangChain
- Vector databases
NICE TO HAVE
- Projects involving chatbots, LLMs, or GenAI applications.
- Exposure to Azure OpenAI, OpenAI APIs, Hugging Face, LangChain, or vector databases.
- Basic knowledge of DevOps or MLOps concepts.
- Familiarity with information retrieval or search.
- Exposure to financial services or regulated industries.
WHAT WILL REALLY CATCH OUR EYE
- Personal or academic AI/GenAI projects.
- Demonstrated ability to learn new tools quickly.
- Clear documentation or presentations of technical work.
- Evidence of collaboration or peer mentoring.
- Passion for solving real-world business problems with technology.