Amazon Web Services (AWS), Application Integration, Application Programming Interface (API), Artificial Intelligence (AI), Big Data, Cloud Computing, Communication Skills, Cross-Functional, Data Quality, Database Extract Transform and Load (ETL), Docker, Machine Learning, Machining Operations, Onboarding, Performance Metrics, Problem Solving Skills, Python Programming/Scripting Language, Quality Management, Sales Pipeline, Software Development, Standards Development, Team Lead/Manager, Team Player
Request ID: 77734-1
Title: AI Engineer:
Locations: Austin, TX
Duration: 6 Months
Salary Range: $53.00- $60.00/Hour on W2 (All inclusive)
Applicants must be able to work on W2 without any Visa sponsorship
Experience Requested- 7+ Years
Job Description:
We are seeking a highly skilled AI Engineer with deep expertise in machine learning operations, cloud-based ETL pipelines, and next-generation AI technologies. The ideal candidate will pilot innovative solutions leveraging Generative AI (GenAI), build and maintain RAG (Retrieval-Augmented Generation) solutions, and collaborate with cross-functional teams to drive data-driven decision-making across the organization.
Key Responsibilities:
- Pilot next-generation technologies to solve complex problems that traditional programming struggles with, using Gen AI or other machine learning techniques.
- Build and maintain RAG solutions to enhance AI-driven applications.
- Develop applications and integrations using Claude, Gemini, or similar LLM SDKs/APIs.
- Design, implement, and manage ETL pipelines on cloud platforms (AWS preferred).
- Use orchestration tools like Airflow and monitoring tools like CloudWatch to manage workflows and notifications.
- Collaborate with cross-functional teams to ensure alignment of ML projects with strategic business goals.
- Develop containerized Python applications to improve data accuracy, accessibility, and reliability.
- Contribute to data governance, improving data quality, standardizing definitions, and onboarding data stewards to manage team KPIs.
Qualifications:
- Proven experience in data engineering, with a strong focus on machine learning operations (MLOps).
- Proficiency in developing ETL pipelines and architecting big data solutions.
- Expertise in at least one cloud platform (AWS preferred) and experience delivering end-to-end projects.
- Strong collaboration and communication skills to work effectively across diverse teams.
- A passion for innovation and the drive to push technological boundaries in ambiguous environments.
Essential Skills:
- Python
- Artificial Intelligence (AI)
- Machine Learning Operations (MLOps)
- ETL Pipeline Development
- Cloud Platforms (AWS preferred)
- Containerization (Docker/Kubernetes)
- Workflow Orchestration (Airflow)
- Monitoring & Alerting (CloudWatch)
Desirable Skills:
- Experience with LLM SDKs/APIs like Claude, Gemini, or similar.
- Familiarity with RAG solutions.
- Strong knowledge of data governance and quality frameworks.