Tekskills Inc.
Artificial Intelligence Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an Artificial Intelligence Engineer in Dallas, TX, for a 12+ month contract, offering a pay rate of "TBD." Candidates must have strong Python skills, AWS experience, and expertise in production ML systems and Agentic AI technologies.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
June 3, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
On-site
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📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
Dallas, TX
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🧠 - Skills detailed
#AWS (Amazon Web Services) #ML (Machine Learning) #SageMaker #Statistics #Cloud #Langchain #Monitoring #Deployment #Lambda (AWS Lambda) #Python #AI (Artificial Intelligence) #S3 (Amazon Simple Storage Service) #Scala
Role description
Job Title: AI Engineer
Location: Dallas , TX (Onsite)
Duration: 12+ Months Contract
IDEAL PROFILE:
Python-first AI Engineer who builds production ML + Agentic AI systems at enterprise scale using AWS.
1. Strong Engineering Foundation (Critical)
- Python is primary language
- Builds scalable backend services/APIs
- Shows performance optimization (latency, throughput)
1. Agentic AI (Top Filter)
- Hands-on with LangChain / AutoGen / CrewAI
- RAG pipelines with vector DBs
- Real use case with impact metrics
1. AWS Cloud Depth
- SageMaker, EKS/ECS, Lambda, S3
- Real deployment examples
1. ML + Statistics Foundations
- Evaluation metrics (precision, recall, F1, AUC)
- ML concepts & algorithms
1. Production ML Systems
- End-to-end lifecycle: training, deployment, monitoring
- Model serving & monitoring
1. Analytical Problem Solving
- Problem → Solution → Impact
- Measurable results
1. Enterprise Platform Experience
- Platform-level systems used across teams
- High-scale, distributed systems
Job Title: AI Engineer
Location: Dallas , TX (Onsite)
Duration: 12+ Months Contract
IDEAL PROFILE:
Python-first AI Engineer who builds production ML + Agentic AI systems at enterprise scale using AWS.
1. Strong Engineering Foundation (Critical)
- Python is primary language
- Builds scalable backend services/APIs
- Shows performance optimization (latency, throughput)
1. Agentic AI (Top Filter)
- Hands-on with LangChain / AutoGen / CrewAI
- RAG pipelines with vector DBs
- Real use case with impact metrics
1. AWS Cloud Depth
- SageMaker, EKS/ECS, Lambda, S3
- Real deployment examples
1. ML + Statistics Foundations
- Evaluation metrics (precision, recall, F1, AUC)
- ML concepts & algorithms
1. Production ML Systems
- End-to-end lifecycle: training, deployment, monitoring
- Model serving & monitoring
1. Analytical Problem Solving
- Problem → Solution → Impact
- Measurable results
1. Enterprise Platform Experience
- Platform-level systems used across teams
- High-scale, distributed systems
