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Ai Implementation Jobs in Mount Pleasant, SC (NOW HIRING)

AI Product Owner - Implement to Renew

SC ยท Remote

$117K - $157K/yr

You will design, prioritize, and deliver the AI-assisted workflows that change how implementation, onboarding, and renewal actually operate, working across business domain leads and the AI Platform ...

Lead Engineer, AI Attack Simulation

Charleston, SC ยท On-site +1

$95K - $126K/yr

You will also establish an AI-first product development workflow, applying AI across discovery, research, solution design, prototyping, implementation, validation, and continuous improvement. The ...

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Ai Implementation information

See Mount Pleasant, SC salary details

$37.3K

$98.9K

$160.6K

How much do ai implementation jobs pay per year?

As of Aug 29, 2026, the average yearly pay for ai implementation in Mount Pleasant, SC is $98,944.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,200.00 and $115,700.00 per year, depending on experience, location, and employer.

What is an AI implementation?

An AI Implementation job involves deploying artificial intelligence solutions within an organization to improve efficiency, automation, and decision-making. Professionals in this role work closely with data scientists, engineers, and business teams to integrate AI models into existing systems. They manage data pipelines, ensure model performance, and address challenges related to scalability and compliance. Strong technical skills, project management, and an understanding of business processes are essential for success in this role.

What are the key skills and qualifications needed to thrive in the AI implementation position?

To excel in AI Implementation, you need a robust understanding of machine learning concepts, data analysis, and software development, often supported by a degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow, cloud platforms (AWS, Azure), and AI integration frameworks is commonly required, along with relevant certifications. Strong project management, problem-solving abilities, and excellent communication skills are crucial for coordinating with stakeholders and driving adoption. Mastering both technical and interpersonal skills ensures projects are delivered effectively and meet business objectives within diverse organizational settings.

What kinds of teams and departments does an AI implementation professional typically collaborate with?

AI Implementation professionals usually work cross-functionally, interacting with data scientists, software engineers, IT departments, and business stakeholders to ensure AI solutions address specific business needs. Regular collaboration with product managers and operations teams helps align technical efforts with strategic objectives and regulatory requirements. You may also work closely with end users to gather feedback, refine implementations, and ensure a smooth adoption process. This collaborative environment not only enhances the quality of AI deployments but also offers valuable exposure to different aspects of the organization, fostering professional growth.

How to become an AI implementation specialist?

To become an AI implementation specialist, individuals typically need a strong background in computer science, data science, or related fields, along with knowledge of machine learning, programming languages like Python, and AI frameworks such as TensorFlow or PyTorch. Gaining experience through internships, certifications, or projects involving AI deployment is also valuable. Continuous learning and staying updated on AI tools and industry trends are essential for success in this role.

How to get into AI implementation?

To pursue a career in AI implementation, develop strong skills in programming languages such as Python, understand machine learning frameworks like TensorFlow or PyTorch, and gain experience with data analysis and model deployment. Earning relevant certifications or degrees in computer science, data science, or AI can also enhance your qualifications.

What are the most commonly searched types of Ai Implementation jobs in Mount Pleasant, SC?

The most popular types of Ai Implementation jobs in Mount Pleasant, SC are:

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For Ai Implementation jobs in Mount Pleasant, SC, the most frequently searched job titles are:

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What cities near Mount Pleasant, SC are hiring for Ai Implementation jobs?

Cities near Mount Pleasant, SC with the most Ai Implementation job openings:

Infographic showing various Ai Implementation job openings in Mount Pleasant, SC as of August 2026, with employment types broken down into 71% Full Time, 25% Part Time, 3% Contract, and 1% Nights. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution, with an average salary of $98,944 per year, or $47.6 per hour.

AI Evaluation Subject Matter Expert

Foxhole Technology

Charleston, SC โ€ข Hybrid

Full-time

Re-posted 7 days ago


Job description

Work Arrangement: Hybrid

Clearance: Active Secret w/TS Capability

Foxhole Technology provides robust cybersecurity and IT support capabilities for federal civilian and defense agencies. A recognized leader in navigating technology and security challenges, Foxhole delivers mission-focused innovations to answer evolving and complex needs. Our talented employee-owners provide agile, scalable services and solutions that solve operational gaps, operate critical systems, and protect and secure the enterprise - across the organization and around the world.

Foxhole Technology is seeking an AI Evaluation SME to join an existing program. The AI Evaluation SME will support the assessment, testing, validation, and operational evaluation of artificial intelligence, machine learning, automation, analytics, and decision-support capabilities being considered for or integrated into the Navy's Next Generation CANES environment. This role will help ensure AI-enabled capabilities are mission-relevant, reliable, secure, explainable, measurable, and suitable for deployment within afloat, tactical, disconnected, intermittent, limited-bandwidth, and multi-security-domain environments.

The SME will develop evaluation frameworks, test methods, metrics, datasets, scenarios, risk assessments, and reporting products that help Navy and CACI stakeholders determine whether AI-enabled capabilities improve network operations, cyber defense, system administration, predictive maintenance, anomaly detection, configuration management, mission planning, or other CANES-related functions.

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KEY RESPONSIBILITIES:ย 

  • Serve as a senior technical advisor for AI evaluation, test planning, performance assessment, and operational suitability analysis in support of Next Generation CANES modernization.
  • Develop AI evaluation strategies, test plans, measures of effectiveness, measures of performance, success criteria, risk indicators, and evaluation scorecards.
  • Assess AI, machine learning, generative AI, automation, analytics, and decision-support capabilities for operational relevance, technical maturity, cyber risk, reliability, maintainability, explainability, human oversight, and fleet suitability.
  • Evaluate AI-enabled tools for use cases such as network monitoring, cyber anomaly detection, event correlation, predictive maintenance, help desk automation, configuration compliance, system health monitoring, log analysis, vulnerability prioritization, and operational decision support.
  • Design test scenarios that reflect Navy afloat operating conditions, including limited bandwidth, disconnected operations, contested cyber environments, cross-domain constraints, variable data quality, and platform-specific operational limitations.
  • Define data requirements, ground truth methods, evaluation datasets, labeling approaches, validation methods, and performance baselines for AI-enabled capabilities.
  • Assess AI model performance using appropriate metrics such as accuracy, precision, recall, false positive rate, false negative rate, latency, robustness, drift, confidence calibration, explainability, and operational impact.
  • Evaluate risks associated with hallucination, model brittleness, adversarial manipulation, data poisoning, prompt injection, bias, over-reliance, model drift, cybersecurity exposure, and failure modes in operational environments.
  • Support AI red teaming, cyber survivability assessment, adversarial testing, safety reviews, and responsible AI evaluation activities.
  • Develop human-machine teaming concepts, operator-in-the-loop workflows, trust calibration approaches, escalation procedures, and recommended guardrails for AI-enabled tools.
  • Produce technical reports, evaluation findings, executive summaries, test observations, data analysis products, and recommendations for Navy and CACI leadership.
  • Collaborate with systems engineers, cybersecurity engineers, software developers, data scientists, network engineers, operational testers, fleet users, and government stakeholders.
  • Support technical interchange meetings, design reviews, test readiness reviews, operational assessments, demonstrations, and acquisition decision support.
  • Provide SME input on AI governance, responsible AI implementation, model lifecycle management, configuration control, sustainment, monitoring, and continuous evaluation.

REQUIRED QUALIFICATIONS:

  • Bachelor's degree in computer science, data science, artificial intelligence, engineering, mathematics, statistics, cybersecurity, operations research, information systems, or a related technical discipline preferred. Advanced degree preferred.
  • Additional years of directly relevant AI evaluation, test, cybersecurity, Navy, or DoD mission system experience may be considered in lieu of a degree.
  • Demonstrated experience evaluating AI, machine learning, data analytics, automation, or decision-support systems in defense, intelligence, cybersecurity, network operations, enterprise IT, or mission system environments.
  • Strong understanding of AI / ML evaluation methods, test design, performance metrics, validation approaches, model limitations, and operational risk assessment.
  • Experience developing test plans, evaluation frameworks, measures of effectiveness, measures of performance, data collection plans, and technical reports.
  • Familiarity with cybersecurity, enterprise networks, tactical networks, system monitoring, anomaly detection, log analytics, or network operations use cases.
  • Ability to assess AI-enabled systems in operationally constrained environments, including limited bandwidth, degraded connectivity, edge computing, and mission-critical infrastructure.
  • Understanding of responsible AI concepts, including transparency, explainability, human oversight, robustness, security, bias, accountability, and lifecycle monitoring.
  • Experience working with cross-functional engineering, cyber, data science, software, test, and government stakeholder teams.
  • Strong written and verbal communication skills, including the ability to brief complex AI evaluation findings to technical and non-technical audiences.
  • Active DoD Secret clearance.

DESIRED QUALIFICATIONS:ย 

  • Experience supporting Navy, DoD, tactical edge, afloat, C4I, cyber, enterprise IT, or mission command systems.
  • Familiarity with CANES, Navy afloat networks, ADNS, NAVWAR programs, RMF, cyber survivability testing, operational test, developmental test, or fleet experimentation.
  • Experience evaluating generative AI, large language models, retrieval-augmented generation, autonomous agents, AI-assisted cyber tools, AI-enabled network operations, or predictive analytics systems.
  • Knowledge of DoD responsible AI guidance, NIST AI Risk Management Framework concepts, RMF, Zero Trust, DevSecOps, MLOps, model monitoring, or secure software supply chain practices.
  • Experience with data analysis tools, scripting, statistical evaluation, dashboards, test automation, or model performance analysis.
  • Experience with AI red teaming, adversarial ML, cyber test events, operational assessments, or acquisition decision support.
  • Top Secret clearance or SCI eligibility.