Gen AI/LLM Engineer; AWS
Job in
Reston, Fairfax County, Virginia, 20194, USA
Listed on 2026-06-02
Listing for:
TriOptus LLC
Full Time
position Listed on 2026-06-02
Job specializations:
-
IT/Tech
AI Engineer, Machine Learning/ ML Engineer, Data Scientist, Data Analyst
Job Description & How to Apply Below
Job Description:
About the Role:
- Client is seeking a highly skilled and motivated AI/ML Engineer to join client's team and drive the development and optimization of AI solutions.
- This role is ideal for someone who thrives at the intersection of machine learning, large language models (LLMs), and cloud infrastructure.
- Candidates will collaborate closely with business stakeholders to design, build, and refine intelligent systems that leverage cutting-edge technologies.
- Collaborate with business teams to understand requirements and translate them into ML models and prompt-based solutions.
- Design, develop, and fine-tune machine learning models, particularly those involving LLMs and generative AI.
- Optimize and adapt prompt engineering strategies to improve model performance and relevance.
- Integrate and deploy models using AWS services including Bedrock, S3, ECS, EC2, Lambda and other AI/ML related services.
- Build and maintain scalable data pipelines and APIs to support ML workflows.
- Monitor model performance and iterate based on feedback and metrics.
- Stay current with advancements in AI/ML and cloud technologies to ensure client's solutions remain cutting-edge.
- Bachelor's or master's degree in computer science, Data Science, Engineering, or a related field.
- 3 plus years of experience in machine learning, data science, or AI engineering.
- Hands-on experience with LLMs (e.g., OpenAI, Anthropic, Cohere) and prompt engineering.
- Strong proficiency in Python and ML libraries (e.g., Tensor Flow, PyTorch, scikit-learn).
- Deep experience with AWS services, especially Bedrock, S3, EC2, and Lambda
- Familiarity with MLOps practices and tools for model deployment and monitoring.
- Excellent problem-solving skills and ability to communicate technical concepts to non-technical stakeholders.
- Strong programming skills in data analytics related languages and libraries, such as Python, R, Pandas, or JavaScript.
- Experience with AWS Sage Maker for model development and model deployment.
- Understanding of quantitative/statistical/ML/AI modeling methodologies.
- Experience in ML engineering, including hands-on experience with Generative AI/LLMs.
- Experience with developing and deploying AI Agents for business problems.
- Experience with fine-tuning or customizing foundation models.
- Knowledge of data privacy and security best practices in cloud environments.
- Familiarity with containerization (Docker) and container orchestration is a plus.
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