GeoSpatial Developer Java - GSJVDV

TekWissen•Phoenix, AZ

20h•Hybrid

About The Position

American Express is seeking a senior engineer specializing in Generative AI automation to support enterprise-wide security initiatives. The role serves as a subject matter expert in Generative AI and agentic engineering, building production-grade agents and automating integrations. It involves designing, building, and operationalizing autonomous AI agents for secure, scalable enterprise automation, managing and reporting on AI-related security risk reduction, and supporting the security champion practice by promoting security principles and controls. The position focuses on productionizing agentic AI solutions and security automation across the software development lifecycle. This includes integrating agents with enterprise systems and security platforms; embedding security into design reviews, code review, CI/CD, and release workflows; establishing agent evaluation and security controls; and providing technical leadership and mentorship. The posting describes the work as hybrid in Phoenix, Arizona.

Requirements

Bachelor’s degree in Cybersecurity, Data Science, Computer Science, or Software Engineering.
10 or more years of experience with automation and development in CI/CD.
10 or more years of software engineering experience.
At least 5 years of cybersecurity experience.
At least 2 years of Generative AI experience.
Hands-on experience delivering agentic AI or AI coding-agent solutions into production, preferably in security, developer productivity, or Secure SDLC workflows.
Demonstrated senior-level experience designing, building, and productionizing autonomous or semi-autonomous AI agents, including planning, tool use, memory and context management, multi-agent orchestration, human-in-the-loop controls, and failure recovery.
Hands-on experience with AI coding and agent platforms such as Anthropic Claude/Claude Code and OpenAI Codex, including prompt and instruction design, tool integration, API/SDK usage, evaluation, guardrails, and enterprise adoption patterns.
Experience building automation tooling for security or developer efficiency.
Proficiency in at least one scripting language: Python, JavaScript, or Bash.
Familiarity with a compiled language such as Go, Rust, or Java.
Experience with GitHub automation and API integrations.
Strong understanding of OWASP Top 10 and industry best practices in Generative AI security.
Knowledge of agent frameworks such as LangGraph, AutoGen, CrewAI, or custom orchestration.
Understanding of AI lifecycle management, including model integration, evaluation, and observability.
Deep expertise in security automation, CI/CD and pull request security integrations, secure-by-design AI architectures, and embedding security across the software lifecycle.
Familiarity with database architectures, including Oracle, SQL, and NoSQL databases.

Nice To Haves

Information security professional certifications, such as SANS GIAC, CISSP, or Generative AI certifications.
Experience mentoring application security and secure development practices.
Master’s degree in Cybersecurity, Data Science, Computer Science, or Software Engineering.
Machine Learning Operations professional certifications.
Strong knowledge of adversarial robustness techniques and tools for machine learning.
Strong knowledge of AI risk management frameworks and trustworthy AI practices.

Responsibilities

Conduct research on emerging threats, vulnerabilities, and technologies to stay current with the security landscape.
Develop and maintain security automation tooling to improve visibility, enforce security best practices, and streamline processes.
Automate secure design reviews and integrate security checks into pull request workflows and CI/CD pipelines.
Design, develop, and operationalize agentic AI systems that autonomously plan, execute, and adapt tasks across complex workflows.
Integrate agents with enterprise systems, APIs, data sources, and security platforms.
Build Secure SDLC agents that support requirements and secure design review, threat modeling, code review, dependency and vulnerability analysis, remediation guidance, pull-request checks, and release/security gates.
Design agents that securely interact with source control, CI/CD, issue tracking, security scanners, cloud services, internal APIs, and developer tooling while enforcing least privilege, secrets protection, authorization boundaries, auditability, and approval workflows.
Create reusable agent tools, skills, workflows, and orchestration patterns using agent frameworks and tool-protocol patterns such as MCP.
Establish agent quality and security evaluation practices covering task success, groundedness, code quality, secure coding, prompt-injection resistance, data leakage, unsafe tool use, permissions, reliability, latency, and cost.
Apply secure-by-design engineering to AI-assisted development, including sandboxing, policy enforcement, telemetry and observability, traceability, red-team testing, and controls for agent-generated code before merge or deployment.
Provide technical leadership and mentorship in agent architecture, AI-assisted engineering, secure coding, and production readiness.
Perform proofs of concept related to security tooling, zero-day vulnerabilities, and emerging risks.
Support the security champion practice by promoting security principles and controls.