Artificial Intelligence (AI) Engineer III

Job Description

Duration: 12 Months Hybrid: 2-3 days per week in office; local candidates Working Hours: 8am – 5pm Travel: 20%, mostly domestic, customer sites or conference Job Summary:

• An AI (Artificial Intelligence) Engineer develops and trains AI models to automate processes and solve complex problems.
• They design and implement AI systems, ensuring they function effectively and align with business objectives.

Responsibilities:

• Evaluate machine learning processes and select appropriate models.
• Collect and analyze large datasets to train AI models.
• Develop and deploy AI algorithms and systems.
• Collaborate with cross functional teams to establish goals for AI processes.
• Test and validate AI models to ensure accuracy and effectiveness.
• Manage data and project infrastructure. Stay updated on the latest AI developments and technologies.

Qualifications:

• Proven experience as an AI Engineer or in a similar role.
• Strong programming skills in languages such as Python, R, or Java.
• Experience with machine learning frameworks and libraries.
• Excellent analytical and problem solving abilities.
• Effective communication and collaboration skills.

Must have:

• Advanced Python
• CI/CD
• CNNs, RNNs, Transformers
• Docker Container
• Docker Swarm
• Kubernetes
• LLM
• REST, gRPC
• vector database

• Strong Large Language Model (LLM) Expertise Hands‐on experience fine‐tuning, adapting, and deploying LLMs, including prompt engineering, embeddings, and context management.
• LLM Application & System Architecture Proven ability to design and implement production‐grade LLM solutions such as RAG pipelines, agents, and tool/function‐calling systems.
• Production MLOps & Model Lifecycle Management Experience owning the end‐to‐end ML lifecycle, including CI/CD, deployment, monitoring, versioning, and performance/cost optimization.
• Advanced Python & Software Engineering Strong Python skills with experience building scalable, testable APIs and services that integrate ML/LLM models into enterprise systems.
• Cloud‐Based Scalable ML Infrastructure Hands‐on experience with AWS, Clienture, or GCP, including containerization (Docker), orchestration (Kubernetes), and GPU‐based ML workloads.

Education:

• Master’s degree in computer science, Engineering, or a related field.

About US Tech Solutions: US Tech Solutions is a global staff augmentation firm providing a wide range of talent on-demand and total workforce solutions. To know more about US Tech Solutions, please visit www.ustechsolutions.com. US Tech Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.