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How much do deployed contractor jobs pay per hour?

As of Sep 3, 2026, the average hourly pay for deployed contractor in Texas is $37.25, according to ZipRecruiter salary data. Most workers in this role earn between $20.08 and $50.52 per hour, depending on experience, location, and employer.

What is a deployed contractor?

A Deployed Contractor is a professional hired to work on-site in a specific location, often internationally or in remote areas, to support a company's operations or government contracts. These roles typically require specialized skills in areas such as security, logistics, IT, or engineering. Deployed Contractors may work under fixed-term contracts and often operate in challenging or high-risk environments. Responsibilities vary by industry but can include maintenance, consulting, training, or operational support.

What are the key skills and qualifications needed to thrive as a deployed contractor?

To thrive as a Deployed Contractor, you need strong technical expertise in your field, relevant industry certifications, and experience working in dynamic environments such as military, government, or construction projects. Familiarity with specialized software, communication tools, safety protocols, and security clearances (as applicable) is often required. Adaptability, cultural sensitivity, and effective problem-solving are key soft skills for excelling under changing conditions and in diverse team settings. These skills and qualities are critical for maintaining operational effectiveness, safety, and collaboration while working on-site, often in remote or challenging locations.

What is the work environment like for a deployed contractor?

As a Deployed Contractor, you can expect to work in varied and sometimes demanding environments, often on-site at client, military, or remote project locations. You will frequently collaborate with multidisciplinary teams, including on-site personnel, project managers, and stakeholders from different organizations. Communication and adaptability are essential, as you may need to adjust quickly to new procedures or cultural expectations based on your deployment location. Teamwork is crucial in this role, and you will regularly coordinate with others to meet project goals and ensure smooth operations.

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Deployed Contractor jobs near you
Infographic showing various Deployed Contractor job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 10% Part Time, and 16% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $77,471 per year, or $37.2 per hour.

Sr Data Scientist - Gen AI ML - Irving

Photon

Irving, TX

Full-time, Contractor

Medical, Dental, Vision, Retirement, PTO

Re-posted 22 days ago

Job description

Role Summary:
We are seeking a Generative AI Engineer to build, optimize, and scale production-ready AI applications. You will design complex multi-agent systems, implement advanced RAG pipelines, and manage the deployment of both frontier and local LLMs. The ideal candidate blends deep machine learning expertise with modern software engineering practices.

Technical Stack:

LLMs: Gemini, OpenAI, Claude, Llama, and Local Model deployment.

Frameworks: LangChain, LlamaIndex, and Hugging Face.

Orchestration: LangGraph and Multi-Agent Systems (MAS).

Development: Python, FastAPI, and Asynchronous Programming.

RAG & Data: PostgreSQL, Vector Databases, and Advanced Retrieval strategies.

ML/DL: PyTorch, TensorFlow, and Model Fine-tuning.

Deployment: Docker, Production API management, and LLM monitoring.

Tools: Prompt Engineering, Workflow Design, and GenAI Optimization.

Key Responsibilities:

Develop and orchestrate sophisticated AI workflows using LangGraph and multi-agent architectures.

Build and maintain Advanced RAG systems utilizing LlamaIndex and vector databases for high-accuracy retrieval.

Integrate and swap diverse LLMs (commercial and open-source) based on performance and cost requirements.

Design and deploy high-performance, scalable backend services using FastAPI and Async Python.

Fine-tune large language models (LLMs) using PyTorch/TensorFlow to improve domain-specific performance.

Optimize GenAI workflows for latency, cost, and reliability using advanced prompt engineering and monitoring tools.

Containerize and deploy AI services via Docker to production environments.

Required Qualifications:

7+ years of experience ; Hands-on experience building and deploying GenAI applications in a production setting.

Strong proficiency in Python and the modern AI library ecosystem (LangChain, LlamaIndex, etc.).

Experience with vector search, embedding models, and advanced data retrieval patterns.

Knowledge of model fine-tuning techniques and local LLM quantization/hosting.

Familiarity with production-grade monitoring, API security, and CI/CD for ML.

Compensation, Benefits and Duration

Minimum Compensation: USD 53,000
Maximum Compensation: USD 188,000
Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role.
Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full time employees.
This position is not available for independent contractors
No applications will be considered if received more than 120 days after the date of this post

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