> Markdown version of [/jobs/ext/3851607-senior-ai-engineer-agentic-ai-enterprise-security](https://www.wearedevelopers.com/jobs/ext/3851607-senior-ai-engineer-agentic-ai-enterprise-security). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Senior AI Engineer - Agentic AI & Enterprise Security

- **Company:** TEKSYSTEMS INC.
- **Location:** Round Rock, TX, United States
- **Experience:** Expert
- **Salary:** $145,600.0
- **Contract:** Temporary contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Automated Storage and Retrieval Systems, Cloud Computing, Continuous Integration, Cursor, Issue Tracking Systems, Python (Programming Language), Open Web Application Security, Systems Development Life Cycle, Software Safety, Secure Coding, Software Engineering, Systems Architecture, Systems Integration, Enterprise Software Applications, Spring Cloud, GitHub Copilot, Large Language Models, Claude Code, Multi-Agent Systems, Prompt Engineering, Software Security, Generative AI, AI Coding Agents, Agentic-AI, Event Driven Architecture, Low Latency, Machine Learning Operations, Evaluation of Large Language Models, Api Design, Model Context Protocol, Devsecops, Security Orchestration, Automation & Response
- **Published:** October 21, 2026
- **Apply:** https://www.careercircle.com/jobs/all/all/usa/tx/round-rock/4f227285-d6ed-438e-9d14-f36297f95dea

## About the Role

* 10-12+ years of software engineering experience
 * 1-3+ years of hands-on AI engineering experience
 * Proven success deploying AI solutions into enterprise production environments
 * Strong security engineering and secure-by-design expertise
 * Experience building agentic systems that operate at scale across business workflows

If you've engineered and deployed autonomous AI solutions that are actively used by large organizations and can clearly articulate the architectural decisions, trade-offs, security considerations, and business impact behind those implementations, we'd love to speak with you., * 10-12+ years of software engineering experience

 * 1-3+ years of dedicated AI engineering experience
 * Proven experience deploying AI applications into enterprise production environments
 * Experience supporting solutions with large-scale organizational adoption, significant transaction volumes, or broad user bases
 * Experience working within large enterprise organizations or highly scalable technology environments

Technical Expertise

 * Strong proficiency with Python and modern software engineering practices
 * Hands-on experience building and deploying autonomous agents and agentic workflows
 * Experience with:
 + Multi-agent systems
 + Agent orchestration
 + Tool/function calling
 + Retrieval-augmented generation (RAG)
 + Context engineering
 + Memory architectures
 + Structured outputs
 + LLM evaluation frameworks
 + LLMOps
 * Deep understanding of:
 + Token optimization and context management
 + API design
 + Scalable system architecture
 + Event-driven systems
 + Cloud-native applications
 * Experience integrating with enterprise systems and platforms

Security & Enterprise Engineering

 * Experience designing solutions that meet enterprise security and compliance standards
 * Understanding of secure development practices and security-first architecture
 * Experience implementing AI governance, guardrails, validation frameworks, or security controls, * Application Security
 * DevSecOps
 * Threat Modeling
 * Secure Software Supply Chain
 * Security Automation
 * AI Safety & AI Governance
 * Security Harness Engineering
 * OWASP Top 10 for LLM Applications
 * NIST Secure Software Development Framework (SSDF)
 * AI coding assistants such as GitHub Copilot, Claude Code, Cursor, or Devin
 * MCP (Model Context Protocol), Individual compensation offered for this position within this range will depend on many factors, including qualifications, skills, relevant experience, job knowledge, geographic location, internal equity, and other pertinent job-related factors.

## Description

Tooling
Research
AI Agents
Operations
Leadership
Governance
Scalability
AI Adoption
Claude Code
GitHub Copilot
Agentic Systems
Security Controls
Business Valuation
Prompt Engineering
Token Optimization
Enterprise Security
Multi-Agent Systems
Security Engineering
Software Engineering
Software Development
Full Stack Development
Artificial Intelligence
Business Transformation
Requirements Elicitation
Business Continuity Planning
Model Context Protocol (MCP)
Python (Programming Language)
Systems Development Life Cycle
Enterprise Application Software
Software Development Life Cycle
Artificial Intelligence Strategy
Artificial Intelligence Infrastructure
Application Programming Interface (API)
Applications Of Artificial Intelligence

At least 12 years
$145,600 / yr
Posted yesterday, * Design, build, and deploy autonomous AI agents that automate and enhance enterprise business workflows

 * Architect multi-agent systems including agent orchestration, tool usage, memory frameworks, retrieval systems, and agent-to-agent communication
 * Develop AI-powered capabilities across the Software Development Lifecycle (SDLC)
 * Build guardrails, security controls, and governance frameworks for AI-generated outputs
 * Create scalable solutions that integrate with enterprise platforms, APIs, CI/CD pipelines, ticketing systems, security tooling, and cloud platforms
 * Optimize context windows, token usage, latency, reliability, and operational costs
 * Collaborate with engineering, security, product, and leadership teams to define AI strategy and implementation roadmaps
 * Establish evaluation frameworks to measure AI accuracy, safety, effectiveness, and business outcomes
 * Mentor teams and help drive adoption of AI engineering best practices across the organization, * Drive AI initiatives from idea to production without constant direction
 * Clearly explain architecture decisions, technical trade-offs, and business outcomes
 * Demonstrate end-to-end ownership of deployed AI solutions
 * Build secure, scalable AI systems used across the enterprise
 * Deliver measurable improvements in productivity, quality, security, or operational efficiency