Senior AI Agent Engineer (Autonomous Remediation & DevSecOps / FTE)

Summary: Design, develop, and harden production-grade AI agents for autonomous remediation and DevSecOps workflows. The role involves building agent orchestration, integrating with CI/CD pipelines, and ensuring secure, governed deployment of AI-driven automation within enterprise environments.

Req ID: 397147

NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now.

We are currently seeking a Senior AI Agent Engineer (Autonomous Remediation & DevSecOps / FTE) to join our team in Charlotte, North Carolina (US-NC), United States (US).

Job Duties and Responsibilities:

Job Description – Senior AI Agent Engineer (Autonomous Remediation & DevSecOps)

• Design, develop, and harden production-grade AI agents across the end-to-end detect → store → plan → remediate → deploy lifecycle.
• Build and orchestrate Finder, Planner, and Executor agents to identify issues, prioritize remediation, execute approved actions, validate changes, and support controlled deployments.
• Develop agent orchestration and tool integrations using Model Context Protocol (MCP), tool calling, agent frameworks, and workflow engines such as Temporal.
• Develop and integrate agents with the Actionable Observation store, Overwatch state machine and prioritization capabilities, and operator console.
• Integrate agents with GitLab pipelines, GitLab CI/CD, JFrog Artifactory, canary deployment workflows, and Tenable Vulnerability Management (UVM) as a vulnerability-finding source.
• Expose and consume enterprise knowledge graphs containing data lineage and environment context through MCP, ensuring agents have governed, read-only access to relevant information.
• Implement event processing, data storage, and state management using Kafka, MongoDB, SQL, and SQLite.
• Develop and query knowledge graphs using Neo4j and Cypher to support contextual retrieval, dependency analysis, and remediation planning.
• Implement automated code-change workflows, AI-assisted code generation, test generation, and lockdown-test practices to validate remediation changes before deployment.
• Apply context engineering and specification-driven development to improve agent accuracy, consistency, traceability, and maintainability.
• Embed human-approval gates, audit trails, access controls, and AI governance controls throughout agent design, execution, and deployment.
• Ensure autonomous workflows comply with enterprise security standards, change-management processes, deployment controls, and production-readiness requirements.
• Support vulnerability remediation and software version-currency initiatives using CVE, EPSS, CVSS, End-of-Life (EOL), and End-of-Support (EOS) considerations.
• Implement controlled deployment patterns, including canary releases and incremental rollouts, to reduce operational risk.
• Troubleshoot agent execution failures, integration issues, workflow exceptions, and deployment problems; perform root-cause analysis and implement corrective actions.
• Monitor and improve agent reliability, performance, scalability, and observability using Dynatrace or comparable tools where applicable.
• Collaborate with application development, infrastructure, cybersecurity, DevSecOps, architecture, and production support teams to integrate agents into existing workflows.
• Document reusable agent patterns, technical designs, integration approaches, governance controls, onboarding procedures, and operational best practices.
• Coach application, infrastructure, and security teams on agent onboarding, secure usage, human oversight, and adoption of the autonomous operating model.
• Participate in technical design reviews, code reviews, automated testing, release planning, and continuous improvement initiatives.
• Own AI agent solutions across requirements, design, development, integration, testing, deployment, monitoring, and ongoing enhancement.

Basic Qualifications: (Required skills with minimum years of experience)

• Minimum 7+ years of experience in software engineering or production application development, delivering and supporting enterprise-grade solutions.
• Minimum 1–2+ years of hands-on experience developing LLM-based applications, Generative AI solutions, AI agents, or agentic workflows.
• Minimum 3+ years of hands-on experience developing production software using Python and/or Java.
• Minimum 3+ years of experience with Git, GitLab CI/CD, automated testing, and software delivery practices.
• Minimum 1+ year of hands-on experience with AI agent orchestration, MCP, tool calling, and agent frameworks or equivalent technologies.
• Minimum 1+ year of experience with agent development platforms such as AWS AgentCore, Kiro, or equivalent technologies.
• Minimum 1+ year of experience with workflow orchestration engines such as Temporal or equivalent platforms.
• Minimum 2+ years of experience developing automated code-change workflows, code validation, automated test generation, or lockdown-test practices.
• Minimum 1+ year of practical experience applying context engineering and specification-driven development to AI or software engineering workflows.
• Minimum 2+ years of experience working with event-processing or data-storage technologies such as Kafka, MongoDB, SQL, or SQLite.
• Minimum 1+ year of experience with Neo4j, Cypher, graph databases, or knowledge-graph querying.
• Minimum 3+ years of experience integrating applications with CI/CD pipelines, artifact repositories, deployment platforms, or enterprise tools.
• Minimum 2+ years of experience implementing secure software engineering practices, access controls, audit trails, or human-in-the-loop approval mechanisms.
• Minimum 1+ year of experience implementing AI governance, security guardrails, or operational controls for AI-driven automation.
• Minimum 3+ years of experience with SDLC, automated testing, change management, release processes, and production support.
• Minimum 3+ years of experience troubleshooting complex application or integration issues, conducting root-cause analysis, and implementing corrective actions.
• Minimum 2+ years of experience collaborating with cross-functional teams, including application development, infrastructure, DevOps, or cybersecurity.
• Minimum 1+ year of experience documenting technical designs, reusable engineering patterns, operational procedures, or implementation standards.
• Minimum 1+ year of experience providing technical guidance, mentoring engineers, or coaching teams on engineering practices or new technology adoption.
• Demonstrated ability to explain personal technical contributions, agent architecture, implementation decisions, challenges, and business outcomes from previous projects.

Travel: NA

Degree:

Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field, or equivalent professional experience.

Nice to Have:

• Experience with vulnerability management, security patching, and software version-currency practices.
• Knowledge of CVE, EPSS, CVSS, EOL, and EOS concepts and their application to vulnerability prioritization.
• Experience with Tenable Vulnerability Management (UVM) and integrating vulnerability findings into automated remediation workflows.
• Experience with the Actionable Observation store, Overwatch state machine, prioritization services, or operator consoles.
• Experience implementing canary deployments, incremental rollouts, automated release controls, and rollback strategies.
• Experience with regulated-environment controls, enterprise AI governance, auditability, and responsible AI practices.
• Experience with Dynatrace or similar application performance monitoring and observability platforms.
• Experience in Financial Services, Banking, Retirement Services, or Wealth Management.
• Additional experience with AWS AgentCore, Kiro, Temporal, MCP-based integrations, and enterprise agent frameworks.
• Experience with Kafka-based event-driven architectures, MongoDB, relational databases, and distributed data processing.
• Experience with Neo4j, Cypher, enterprise knowledge graphs, data lineage, and environment dependency mapping.
• Experience leading technical design discussions, establishing reusable engineering standards, and mentoring application, infrastructure, and security teams.

#LI-NorthAmerica

NTT DATA provides a reasonable range of compensation for U.S.-based positions. The starting pay range for this role is $102,675.00 - $171,125.00. Actual compensation will depend on a number of factors, including the candidate’s relevant experience, technical skills, and other qualifications.

This position may also be eligible for incentive compensation based on individual and/or company performance.

This position is eligible for company benefits including medical, dental, and vision insurance with an employer contribution, flexible spending or health savings account, life and AD&D insurance, short and long term disability coverage, paid time off, employee assistance, participation in a 401k program with company match, and additional voluntary or legally-required benefits.

About NTT DATA

NTT DATA is a $30 billion business and technology services leader, serving 75% of the Fortune Global 100. We are committed to accelerating client success and positively impacting society through responsible innovation. We are one of the world's leading AI and digital infrastructure providers, with unmatched capabilities in enterprise-scale AI, cloud, security, connectivity, data centers and application services. our consulting and Industry solutions help organizations and society move confidently and sustainably into the digital future. As a Global Top Employer, we have experts in more than 50 countries. We also offer clients access to a robust ecosystem of innovation centers as well as established and start-up partners. NTT DATA is a part of NTT Group, which invests over $3 billion each year in R&D.

Whenever possible, we hire locally to NTT DATA offices or client sites. This ensures we can provide timely and effective support tailored to each client’s needs. While many positions offer remote or hybrid work options, these arrangements are subject to change based on client requirements. For employees near an NTT DATA office or client site, in-office attendance may be required for meetings or events, depending on business needs. At NTT DATA, we are committed to staying flexible and meeting the evolving needs of both our clients and employees. NTT DATA recruiters will never ask for payment or banking information and will only use @nttdata.com, @nttdatafed.com and @talent.nttdataservices.com email addresses. If you are requested to provide payment or disclose banking information, please submit a contact us form, https://us.nttdata.com/en/contact-us.

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