{"schemaVersion":"jobsearcher.job.v1","id":"c4ff84e7f565973e777f7c75","url":"https://jobsearcher.com/jobs/c4ff84e7f565973e777f7c75","canonicalUrl":"https://jobsearcher.com/jobs/c4ff84e7f565973e777f7c75","title":"Artificial Intelligence/Machine Learning Engineer","description":"Artificial Intelligence/Machine Learning Engineer\r\nAustin, United States | Posted on 06/17/2026\r\nClient Name Texas Department of Information Resources\r\nDate Opened 06/17/2026\r\nJob Type Contract\r\nRequired Skills\r\nrapid prototyping\r\nproduction deployment\r\n\r\n21\r\n\r\nWork Location Arrangement Hybrid\r\nWork Experience 8 years\r\nApplication Deadline 06/24/2026 17:00\r\nNo. of Hours 500\r\nTarget Date 07/13/2026\r\nContract End Date 10/31/2026\r\nIndustry Government & Public Sector\r\nNumber of Positions 2\r\nCity Austin\r\nState/Province Texas\r\nCountry United States\r\nJob Description\r\nThe Artificial Intelligence/Machine Learning Engineer will support the Texas Department of Information Resources on the Forward Deployed Engineer (FDE) initiative. This role works directly with DIR and partner agencies to rapidly design, build, deploy, and iterate modern digital solutions, often working onsite or embedded with mission teams. The position combines hands-on engineering, rapid prototyping, and production deployment to accelerate modernization and reduce reliance on legacy integrator models. The engineer will bridge product, security, business, and cloud engineering teams, evaluating AI/LLM capabilities based on business need, security posture, data classification, interoperability, and total cost of ownership rather than defaulting to a single vendor or platform. The role also includes delivering knowledge transfer sessions and coaching internal agency staff to build long-term technical capability. This position requires the ability to translate ambiguous problems into practical, AI-enabled workflows while preserving architectural flexibility.\r\nResponsibilities\r\nDeliver high-quality application, API, Model Context Protocol (MCP), and automation components using cloud-native architectures.\r\nDevelop rapid prototypes, pilots, and production systems using modern engineering patterns.\r\nIntegrate systems across agencies using secure, scalable, human-in-the-loop workflows.\r\nImplement DevSecOps automation, including CI/CD, infrastructure as code, and container orchestration.\r\nCollaborate directly with agency stakeholders to gather requirements and convert them into working software.\r\nDeploy AI-enabled development workflows and LLM-assisted capabilities.\r\nTroubleshoot complex production issues and lead root-cause analysis.\r\nMentor agency developers to mature internal capability and reduce vendor reliance.\r\nProvide documentation, architectural guidance, and knowledge transfer to agency staff.\r\nBuild AI-powered tools using existing systems and create new applications to move from experimentation to real-world impact.\r\nRequirements\r\nMinimum Qualifications: Candidates must meet all minimum qualifications\r\n8 years of hands-on software engineering experience.\r\n8 years of expertise in modern cloud platforms.\r\n8 years of experience integrating APIs, including LLMs, internal services, and data platforms.\r\n8 years of experience with CI/CD platforms such as GitHub Actions or Azure DevOps, including building and deploying applications.\r\n8 years of experience with infrastructure as code and environment automation tools such as Terraform or ARM/Bicep, including experience working directly with customers or frontline operational teams to build and improve solutions.\r\n8 years of experience extending tools such as Salesforce, Appian, or ServiceNow, with demonstrated success delivering systems end-to-end from design through deployment.\r\n8 years of experience with security frameworks such as NIST, Zero Trust, and TX-RAMP expectations.\r\n8 years of experience with cross-functional collaboration and communication in a technical environment.\r\nDemonstrated ability to determine when not to use low-code solutions.\r\nDemonstrated ability to identify high-value use cases and observe workflows.\r\nBachelor's degree in Computer Science, Engineering, or a related field, or 10 years of equivalent hands-on experience in modern engineering roles.\r\nPreferred Qualifications\r\nExperience in state government, regulated environments, or multi-agency integration projects.\r\nPrior Forward Deployed Engineer (FDE) or technical field engineering experience at a software platform company.\r\nExperience designing, evaluating, or implementing AI-enabled workflows using commercial, open-source, or government-approved LLM platforms, including retrieval-augmented generation, agentic workflows, model evaluation, prompt management, human-in-the-loop review, and responsible AI controls.\r\nExperience with shared technical services or modernization programs, such as TSS/MSI.\r\nExperience producing reusable components, design systems, and developer tooling.\r\nAbility to compare AI/LLM options using objective criteria such as data sensitivity, hosting model, latency, cost, accuracy, explainability, auditability, security controls, integration complexity, and operational sustainability.\r\nCISSP, CCSP, or CISM certification.\r\nTOGAF or other architecture certification.\r\nScrum Master or SAFe Agile certification.\r\nTX-RAMP knowledge or auditor training.\r\nCloud architecture, DevOps, AI, security, or Kubernetes certification from a major provider such as Azure, AWS, Google Cloud, Kubernetes, HashiCorp, ISC2, or ISACA.\r\nAdditional Requirements\r\nCandidates must currently reside within 50 miles of the Austin, Texas work location. Out-of-state candidates or those planning to relocate will not be considered.\r\nCriminal background check requirements as authorized by Texas law.\r\nContract is initially for 90 days, with extensions possible.\r\nCandidate must be able to work outside normal business hours, including weekends, evenings, and holidays, as requested and pre-approved by the agency.\r\nWork Location and Schedule\r\nLocation: Austin, Texas 78758\r\nSchedule: Monday through Friday, 8:00 AM to 5:00 PM, excluding State holidays.\r\nWork Arrangement: Hybrid, on-site 3 days per week with telework for remaining days.\r\nAir InfoSec, LLC is an Equal Opportunity Employer and does not discriminate on the basis of race or ethnicity, religion, sex, national origin, age, veteran disability or genetic information or any other reason prohibited by law in employment.\r\nJ-18808-Ljbffr","company":"Airinfosec","rawCompany":"airinfosec","city":"Austin","state":"TX","isRemote":false,"isActive":false,"createdAt":"2026-06-25T01:21:43.139Z","occupations":[{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1211.00","title":"Computer Systems Analysts","slug":"computer-systems-analysts"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Artificial Intelligence/Machine Learning Engineer","description":"Artificial Intelligence/Machine Learning Engineer\r\nAustin, United States | Posted on 06/17/2026\r\nClient Name Texas Department of Information Resources\r\nDate Opened 06/17/2026\r\nJob Type Contract\r\nRequired Skills\r\nrapid prototyping\r\nproduction deployment\r\n\r\n21\r\n\r\nWork Location Arrangement Hybrid\r\nWork Experience 8 years\r\nApplication Deadline 06/24/2026 17:00\r\nNo. of Hours 500\r\nTarget Date 07/13/2026\r\nContract End Date 10/31/2026\r\nIndustry Government & Public Sector\r\nNumber of Positions 2\r\nCity Austin\r\nState/Province Texas\r\nCountry United States\r\nJob Description\r\nThe Artificial Intelligence/Machine Learning Engineer will support the Texas Department of Information Resources on the Forward Deployed Engineer (FDE) initiative. This role works directly with DIR and partner agencies to rapidly design, build, deploy, and iterate modern digital solutions, often working onsite or embedded with mission teams. The position combines hands-on engineering, rapid prototyping, and production deployment to accelerate modernization and reduce reliance on legacy integrator models. The engineer will bridge product, security, business, and cloud engineering teams, evaluating AI/LLM capabilities based on business need, security posture, data classification, interoperability, and total cost of ownership rather than defaulting to a single vendor or platform. The role also includes delivering knowledge transfer sessions and coaching internal agency staff to build long-term technical capability. This position requires the ability to translate ambiguous problems into practical, AI-enabled workflows while preserving architectural flexibility.\r\nResponsibilities\r\nDeliver high-quality application, API, Model Context Protocol (MCP), and automation components using cloud-native architectures.\r\nDevelop rapid prototypes, pilots, and production systems using modern engineering patterns.\r\nIntegrate systems across agencies using secure, scalable, human-in-the-loop workflows.\r\nImplement DevSecOps automation, including CI/CD, infrastructure as code, and container orchestration.\r\nCollaborate directly with agency stakeholders to gather requirements and convert them into working software.\r\nDeploy AI-enabled development workflows and LLM-assisted capabilities.\r\nTroubleshoot complex production issues and lead root-cause analysis.\r\nMentor agency developers to mature internal capability and reduce vendor reliance.\r\nProvide documentation, architectural guidance, and knowledge transfer to agency staff.\r\nBuild AI-powered tools using existing systems and create new applications to move from experimentation to real-world impact.\r\nRequirements\r\nMinimum Qualifications: Candidates must meet all minimum qualifications\r\n8 years of hands-on software engineering experience.\r\n8 years of expertise in modern cloud platforms.\r\n8 years of experience integrating APIs, including LLMs, internal services, and data platforms.\r\n8 years of experience with CI/CD platforms such as GitHub Actions or Azure DevOps, including building and deploying applications.\r\n8 years of experience with infrastructure as code and environment automation tools such as Terraform or ARM/Bicep, including experience working directly with customers or frontline operational teams to build and improve solutions.\r\n8 years of experience extending tools such as Salesforce, Appian, or ServiceNow, with demonstrated success delivering systems end-to-end from design through deployment.\r\n8 years of experience with security frameworks such as NIST, Zero Trust, and TX-RAMP expectations.\r\n8 years of experience with cross-functional collaboration and communication in a technical environment.\r\nDemonstrated ability to determine when not to use low-code solutions.\r\nDemonstrated ability to identify high-value use cases and observe workflows.\r\nBachelor's degree in Computer Science, Engineering, or a related field, or 10 years of equivalent hands-on experience in modern engineering roles.\r\nPreferred Qualifications\r\nExperience in state government, regulated environments, or multi-agency integration projects.\r\nPrior Forward Deployed Engineer (FDE) or technical field engineering experience at a software platform company.\r\nExperience designing, evaluating, or implementing AI-enabled workflows using commercial, open-source, or government-approved LLM platforms, including retrieval-augmented generation, agentic workflows, model evaluation, prompt management, human-in-the-loop review, and responsible AI controls.\r\nExperience with shared technical services or modernization programs, such as TSS/MSI.\r\nExperience producing reusable components, design systems, and developer tooling.\r\nAbility to compare AI/LLM options using objective criteria such as data sensitivity, hosting model, latency, cost, accuracy, explainability, auditability, security controls, integration complexity, and operational sustainability.\r\nCISSP, CCSP, or CISM certification.\r\nTOGAF or other architecture certification.\r\nScrum Master or SAFe Agile certification.\r\nTX-RAMP knowledge or auditor training.\r\nCloud architecture, DevOps, AI, security, or Kubernetes certification from a major provider such as Azure, AWS, Google Cloud, Kubernetes, HashiCorp, ISC2, or ISACA.\r\nAdditional Requirements\r\nCandidates must currently reside within 50 miles of the Austin, Texas work location. Out-of-state candidates or those planning to relocate will not be considered.\r\nCriminal background check requirements as authorized by Texas law.\r\nContract is initially for 90 days, with extensions possible.\r\nCandidate must be able to work outside normal business hours, including weekends, evenings, and holidays, as requested and pre-approved by the agency.\r\nWork Location and Schedule\r\nLocation: Austin, Texas 78758\r\nSchedule: Monday through Friday, 8:00 AM to 5:00 PM, excluding State holidays.\r\nWork Arrangement: Hybrid, on-site 3 days per week with telework for remaining days.\r\nAir InfoSec, LLC is an Equal Opportunity Employer and does not discriminate on the basis of race or ethnicity, religion, sex, national origin, age, veteran disability or genetic information or any other reason prohibited by law in employment.\r\nJ-18808-Ljbffr","datePosted":"2026-06-25T01:21:43.139Z","dateModified":"2026-06-25T01:21:43.139Z","hiringOrganization":{"@type":"Organization","name":"Airinfosec","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Austin","addressRegion":"TX","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"c4ff84e7f565973e777f7c75"},"url":"https://jobsearcher.com/jobs/c4ff84e7f565973e777f7c75"}}