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Assistant Ai Strategy Jobs in Kansas (NOW HIRING)

Atlas HXM

$98K - $134K/yr

Design and implement secure architectures for enterprise AI platforms, AI assistants, AI APIs, and ... Evaluate new AI technologies and recommend secure adoption strategies based on business needs and ...

Human Agency

Every product, strategy, or asset we create must be both beautiful and functional; practical ... Design end-to-end processes that embed AI tools (LLMs, automation platforms, knowledge assistants ...

Evergy

Corporate Strategy Analyst

Topeka, KS

$61K - $76K/yr

... metrics. Assist in reducing data silos across the business and work closely with Evergy ... Identify, evaluate, and utilize AI-enabled technologies and automation tools to enhance business ...

New

Evergy

Corporate Strategy Analyst

Topeka, KS · On-site

$61K - $76K/yr

... metrics. Assist in reducing data silos across the business and work closely with Evergy ... utilize AI-enabled technologies and automation tools to enhance business processes, improve ...

New

Evergy

Corporate Strategy Analyst

Topeka, KS

$61K - $76K/yr

... metrics. Assist in reducing data silos across the business and work closely with Evergy ... Identify, evaluate, and utilize AI-enabled technologies and automation tools to enhance business ...

New

Parexel

... assistants, and other small-scale automation -- while enabling business super-users to build their own solutions. This position plays a key role in delivering strategic AI and automation value ...

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Assistant Ai Strategy information

How do I become an assistant AI strategist?

To become an assistant AI strategist, develop a strong foundation in artificial intelligence, machine learning, and data analysis through relevant degrees or certifications. Gaining experience with AI tools, programming languages like Python, and understanding business applications of AI can enhance your qualifications for this role.

What are some typical challenges an assistant AI strategy professional might face when supporting the development and implementation of AI initiatives?

As an Assistant AI Strategy professional, you'll often encounter challenges such as aligning AI initiatives with overall business objectives, managing stakeholder expectations, and navigating evolving technologies. You may also need to balance the need for innovation with concerns about data privacy, ethical use, and regulatory compliance. Collaborating effectively across technical, business, and operations teams is crucial to ensure the successful integration of AI solutions within existing workflows.

What is the easiest assistant AI strategy job to get into?

Entry-level assistant AI strategy roles typically require a basic understanding of AI concepts, data analysis, and familiarity with tools like Python or machine learning platforms. Gaining relevant certifications or completing online courses can improve chances, and internships or junior positions often serve as accessible entry points into the field.

What is an assistant AI strategy?

An Assistant AI Strategy refers to the planning and implementation of artificial intelligence technologies, such as digital assistants, to support and enhance business operations. This role involves analyzing current AI trends, identifying opportunities for AI integration, and recommending best practices for deploying AI assistants. The goal is to improve efficiency, automate routine tasks, and provide valuable insights for decision-making. Professionals in this field work closely with technical teams and business stakeholders to align AI initiatives with organizational objectives.

What is the difference between Assistant Ai Strategy vs Data Analyst?

AspectAssistant Ai StrategyData Analyst
Required CredentialsBachelor's in Computer Science, AI, or related fields; familiarity with AI toolsBachelor's in Statistics, Data Science, or related fields; proficiency in data analysis tools
Work EnvironmentTech companies, AI startups, R&D teamsBusiness, finance, healthcare, and other industries
Employer & Industry UsagePrimarily in AI-focused roles within tech and innovation sectorsAcross various industries for data-driven decision making

The Assistant Ai Strategy role focuses on developing and implementing AI strategies, working closely with AI teams, and understanding AI technologies. In contrast, a Data Analyst primarily interprets data, creates reports, and supports business decisions through data insights. While both roles require analytical skills, Assistant Ai Strategy emphasizes AI knowledge and strategic planning, whereas Data Analysts focus on data manipulation and analysis.

What are the key skills and qualifications needed to thrive as an assistant AI strategist, and why are they important?

To thrive as an Assistant AI Strategist, you need a solid understanding of artificial intelligence concepts, data analysis, and strategic planning, often supported by a degree in computer science, data science, or business. Familiarity with tools like Python, machine learning platforms (such as TensorFlow or Azure ML), and data visualization software is commonly required. Strong communication, critical thinking, and collaborative skills help you effectively bridge technical teams and business stakeholders. These skills ensure successful AI project implementation and alignment with organizational goals.
What are the most commonly searched types of Ai Strategy jobs in Kansas? The most popular types of Ai Strategy jobs in Kansas are:
What job categories do people searching Assistant Ai Strategy jobs in Kansas look for? The top searched job categories for Assistant Ai Strategy jobs in Kansas are:
What cities in Kansas are hiring for Assistant Ai Strategy jobs? Cities in Kansas with the most Assistant Ai Strategy job openings:
Assistant Ai Strategy jobs near you
Infographic showing various Assistant Ai Strategy job openings in Kansas as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, 1% Temporary, and 2% Contract. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution.

Senior Security Engineer, AI & DevSecOps

Atlas HXM

$98K - $134K/yr

Full-time

Posted 26 days ago

Job description

Role Overview

We are seeking a forward-thinking Senior Security Engineer, AI & DevSecOps to help shape the future of secure AI adoption across the organization.

As part of the Information Security team, you will build and secure the platforms, processes, and governance that enable developers and business teams to safely leverage artificial intelligence. You'll work at the intersection of AI, application security, cloud security, and DevSecOps.

This role is ideal for someone who thrives on emerging technologies, understands how modern platforms connect through APIs and automation, and can translate security requirements into scalable, developer-friendly solutions.

Key Responsibilities
  • Design and implement secure architectures for enterprise AI platforms, AI assistants, AI APIs, and AI-enabled applications.
  • Build and maintain a secure AI sandbox environment supporting experimentation and responsible AI adoption.
  • Develop security guardrails for AI-assisted development, including AI-generated code, vibe coding, AI agents, and AI workflows.
  • Evaluate new AI technologies and recommend secure adoption strategies based on business needs and risk.
  • Integrate security throughout the Secure Software Development Lifecycle (SSDLC) using automated controls and developer-friendly workflows.
  • Integrate SAST, DAST, SCA, secret scanning, IaC scanning, and cloud security scanning into CI/CD pipelines.
  • Secure cloud-native applications, APIs, containers, and AI services across Azure, AWS, and GCP.
  • Review AI applications, integrations, and AI-generated solutions prior to production deployment.
  • Perform AI security assessments, threat modeling, and architecture reviews.
  • Support vulnerability management, incident response, and threat detection involving AI platforms and cloud services.
  • Support change management, configuration management, documentation, and audit evidence.
  • Support ISO/IEC 27001, 27017, 27018, and future AI governance initiatives.
  • Partner with engineering teams to enable secure development while minimizing friction.
  • Continuously research emerging AI technologies, threats, and best practices.
Required Qualifications
  • 7-12+ years of experience in cybersecurity, application security, DevSecOps, cloud security, platform engineering, or related disciplines.
  • Demonstrated experience securing enterprise AI platforms, AI APIs, AI-assisted development tools, or LLM ecosystems.
  • Deep understanding of modern AI security concepts, including prompt injection, data leakage, AI supply chain risks, and responsible AI practices.
  • Strong understanding of how cloud platforms, APIs, identity, data, and AI services integrate to deliver secure enterprise solutions.
  • Experience integrating security into modern software delivery pipelines using automated testing and policy enforcement.
  • Hands-on experience with application security, cloud security, vulnerability management, and developer security platforms.
  • Experience implementing IAM, Zero Trust principles, logging, monitoring, and security automation.
  • Experience supporting governance frameworks including ISO/IEC 27001, 27017, 27018, NIST CSF, or SOC 2.
  • Strong automation and scripting skills using Python, PowerShell, Bash, or REST APIs.
  • Excellent communication skills, with the ability to translate security requirements into practical engineering solutions.
Preferred Qualifications
  • Experience securing AI agents, MCP integrations, RAG solutions, vector databases, or AI orchestration platforms.
  • Experience implementing AI governance programs and enterprise AI security standards.
  • Experience performing threat modeling, application security assessments, and architecture reviews.
  • Experience supporting internal and external compliance audits.
  • Professional certifications such as CISSP, CCSP, CISM, Azure Security Engineer Associate, or AWS Certified Security - Specialty.
Tools & Technologies

Experience with one or more of the following is preferred:

  • Source Control & CI/CD: GitHub Enterprise, GitHub Actions, Azure DevOps, GitLab, Jenkins
  • Application Security: GitHub Advanced Security, SonarQube, SonarCloud, Snyk, Checkov, DefectDojo
  • Cloud Security: Wiz, Microsoft Defender for Cloud, Microsoft Defender XDR, Microsoft Sentinel, SentinelOne
  • Cloud Platforms: Microsoft Azure, AWS, Google Cloud Platform (GCP)
  • Identity & Access: Microsoft Entra ID
  • Data Protection: Microsoft Purview, Microsoft Defender for Cloud Apps, Microsoft Intune
  • AI Platforms: ChatGPT Enterprise, Microsoft Copilot, Google Gemini, Claude, Azure AI Foundry, AI agents, MCP integrations
  • Automation: Python, PowerShell, Bash, REST APIs

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