Applied AI Engineer

Role Summary

At McAfee, you'll be the technical backbone of the AI Center of Excellence — the point person for McAfee's AI Ops infrastructure and the personal scout on everything new in the AI ecosystem. You will own the platforms the rest of the company builds AI on, including the AI Gateway and AI Factory, managing them day-to-day and evolving them as demand grows. Working with InfoSec on policy and Cloud Infrastructure on the underlying platform, you will help keep McAfee's AI foundation secure, reliable, and ready to scale. You will also continuously scan the AI frontier for new models, tools, frameworks, and agentic patterns, form a fast and opinionated view of what matters to McAfee, recommend what's worth a proof of concept, and be technically deep enough to stand it up and prove it yourself. This is a Hybrid position based in Frisco, TX. We are only considering candidates within a commutable distance to the Frisco office. You will be required to be onsite on an as‑needed basis; when not working onsite, you will work from your home office. We are not offering relocation assistance.

Position Details

About the Role:

• You will serve as the point person for the AI Center of Excellence's infrastructure needs — the platforms McAfee's AI capabilities run on.
• You will manage the AI Gateway — including logging, model routing, and budget thresholds/cost controls — working with InfoSec on policy and Cloud Infrastructure on the underlying platform to keep it secure, reliable, and cost-attributed.
• You will build and maintain McAfee's MCP factory and skills factory — the reusable MCP servers, skills, and plugins that let the CoE and business teams build agents faster and more consistently.
• You will own the McAfee MCP roster and skills registry, running the intake, prioritization, vetting, and publishing pipeline in partnership with InfoSec, and serving as the primary owner for pushing new, approved skills and MCPs live to the AI Tool Hub.
• You will map legacy tools and integrations into the new skills/MCP catalog structure as part of migrating the company onto AI CoE-supported tooling.
• You will evolve the AI infrastructure as demand grows, scaling capacity, adding capabilities, and hardening reliability as agent volume increases across the company.
• You will drive model routing across model providers (e.g., AWS Bedrock, Claude Enterprise), partnering with Cloud Infrastructure to solve for reliability and observability as usage scales.
• You will continuously scan the AI frontier — models, frameworks, agentic patterns, open‑source shifts — and maintain McAfee's AI Tech Radar on a biweekly cadence.
• You will surface what matters to the Head of AI CoE with a concise, opinionated take: what it does, whether McAfee should care, and how quickly a POC could stand up.
• You will recommend and feed the POC pipeline, with at least half of candidates originating from your own scouting rather than inbound requests.
• You will build and stand up whatever is selected for a POC, configuring it for McAfee's environment, stress‑testing it, and reporting back with an honest go/no‑go.
• You will prove new capabilities end to end at prototype depth — enough to make a confident recommendation, not to run in production.
• You will work closely with InfoSec throughout the POC process, engaging them early on security review, data handling, and risk so a promising tool clears the bar before it advances.
• You will build custom MCP servers, integrations, and prototypes as needed to test a capability properly.
• You will deliver technical demos to senior leadership, including VPs and the CIO — working prototypes, not slides about what could be built.
• You will stay genuinely current on AI developments and translate that awareness into practical action for the team.

About You:

• You have strong hands‑on experience building agents, including with coding agents such as Claude Code, Codex, or similar.
• You have hands‑on experience standing up and managing AI or platform infrastructure, such as API gateways, model‑access layers, or comparable production services.
• You have experience managing or operating an AI gateway (or comparable API/model‑access gateway) — a core function of this role.
• You have proficiency in at least one general‑purpose programming language commonly used for building MCP servers and integrations, such as Python and/or TypeScript/Node.js.
• You have hands‑on experience with a major cloud platform including deploying and operating services in production.
• You have experience designing or integrating REST APIs, including authentication patterns (OAuth, API keys) and webhook‑based integrations.
• You have experience with observability and monitoring tooling (logging, metrics, alerting).
• You have working knowledge of security and data‑handling fundamentals — secrets and access management, data handling policies, and awareness of AI‑specific risks such as prompt injection and data leakage.
• You have a strong understanding of the AI model landscape, including the strengths, weaknesses, and appropriate use cases for GPT, Claude, Gemini, and leading open‑source models.
• You are comfortable building and maintaining MCP servers and working with tool‑calling patterns.
• You are able to present and demo to senior leadership — this role regularly presents to Directors, VPs, and the CIO.
• You have strong written communication skills — POC findings and Tech Radar updates must be clear and actionable.
• You already follow AI developments proactively — you've tried the latest framework before being asked to, have opinions on model benchmarks, and can tell in two minutes whether something is real or hype.
• Experience managing structured intake, vetting, and publishing pipelines for developer tools or integrations is a plus.
• Experience with infrastructure‑as‑code (e.g., Terraform) and production reliability practices such as monitoring, alerting, and incident response is a plus.
• Experience designing evaluation frameworks or benchmarks to support structured, defensible go/no‑go decisions is a plus.
• Experience with enterprise agent platforms is a plus.
• Familiarity with McAfee's technology stack (AWS, GitHub, Jira, JFrog, Confluence, Claude) is a plus.
• Experience evaluating and recommending AI tools in a structured enterprise context is a plus.

#LI-Hybrid

Company Overview

McAfee is a leader in personal security for consumers. Focused on protecting people, not just devices, McAfee consumer solutions adapt to users’ needs in an always online world, empowering them to live securely through integrated, intuitive solutions that protects their families and communities with the right security at the right moment.

Company Benefits and Perks

We work hard to embrace diversity and inclusion and encourage everyone at McAfee to bring their authentic selves to work every day. We offer a variety of social programs, flexible work hours and family‑friendly benefits to all of our employees.:

• Bonus Program
• 401k Retirement
• Medical, Dental, Vision, Basic Life, Short Term Disability and Long‑Term Disability Coverage
• Paid Parental Leave
• Support and Community Involvement
• 14 Paid Company Holidays
• Unlimited Paid Time Off for Exempt Employees
• 96 Hours of Sick Time and 120 Hours of Vacation for Non‑Exempt Employees Accrued Each Year

We're serious about our commitment to diversity which is why McAfee prohibits discrimination based on race, color, religion, gender, national origin, age, disability, veteran status, marital status, pregnancy, gender expression or identity, sexual orientation or any other legally protected status.

Pay Range

The anticipated compensation for this position is USD $109,240.00/Yr. - USD $179,462.50/Yr. depending on experience and qualifications.

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