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# GenAI Engineer

- **Company:** Omm IT Solutions
- **Location:** United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Training Data, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Software Applications, Artificial Neural Networks, Microsoft Azure, Cloud Engineering, Code Generation, Continuous Integration, Data Cleansing, Data Transformation, Python (Programming Language), Machine Learning, Natural Language Processing, Performance Tuning, Tensorflow, Software Engineering, Software Organization, Scripting, Feature Engineering, Pytorch, Large Language Models, Prompt Engineering, Deep Learning, Generative AI, Keras, Scikit Learn, Information Technology, Data Management, Variational Autoencoders, Machine Learning Operations, Software Version Control
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/genai-engineer-woodlawn-md--6b167af4-f06b-4df8-91d2-f0e2fc86e794

## About the Role

MD5 (Message Digest Algorithm 5), Machine Learning, Python Programming/Scripting Language, Data Management, Natural Language Processing (NLP), Software Engineering, Deep Learning, Training Data Sets, Performance Tuning/Optimization, Content Development, * Machine Learning, Deep Learning, Neural Networks, Python, Natural Language Processing, Prompt Engineering, and Data Management and Preprocessing., * Bachelor's Degree in Computer Science, Mathematics, Engineering or a related field.

 * Masters or Doctorate degree may substitute for required experience
 * Minimum 5 years of hands-on experience designing, developing, and implementing AI models (Generative AI experience preferred)
 * Must be able to obtain and maintain a Public Trust. Contract requirement.

Required Skill

 * Strong foundation in Machine Learning, Deep Learning, and neural networks (GANs, VAEs, Transformers, LLMs).
 * Proficiency in programming languages, especially Python, and relevant libraries (Scikit-Learn, TensorFlow, PyTorch, Keras).
 * Expertise in Natural Language Processing (NLP) for text and language generation.
 * Data management, preprocessing, and feature engineering skills.
 * Expertise with prompt engineering techniques for guiding AI models.
 * Experience with cloud-based AI platforms (AWS, Azure).
 * Knowledge of software development best practices, including CI/CD pipelines, version control, and testing.
 * Problem-solving, analytical, and critical thinking skills.
 * Strong communication and collaboration abilities.
 * Understanding of AI ethics and responsible AI development.

Desired Skills

 * Prior experience with federal or state governments IT projects.
 * Familiarity with various LLM models available in the market
 * Working knowledge of Retrieval Augmented Generation (RAG) to enhance LLM responses
 * Experience integrating GenAI models and services into existing applications using APIs

## Description

* Design and develop generative models: This includes working with architectures like GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and especially transformer-based models (like those behind LLMs).
 * Fine-tuning and optimization: Adapting pre-trained generative models for specific tasks and datasets, optimizing their performance, efficiency, and the quality of their generated output.
 * Prompt engineering: Crafting and refining prompts to guide generative models to produce desired outputs, often for specific applications (e.g., content creation, code generation, design).
 * Build AI pipelines: Creating the infrastructure and workflows for data preparation, model training, deployment, and ongoing monitoring of generative AI systems.
 * Integration: Incorporating generative AI models into existing software applications and products.
 * Research and experimentation: Staying up to date with the latest research in generative AI and experimenting with new algorithms and techniques.
 * Ethical considerations: Understanding and addressing potential biases, misuse, and ethical implications of generative AI.
 * All other duties as assigned or directed.