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Job Description
Senior Lead AI/ML and Full Stack Engineer - R01567102
Miami, US Job ID:
R01567102
Senior Lead AI/ML and Full Stack Engineer - R01567102
About Brillio:
Brillio is one of the fastest growing digital technology service providers and a partner of choice for many Fortune 1000 companies seeking to turn disruption into a competitive advantage through innovative digital adoption. Brillio, renowned for its world-class professionals, referred to as "Brillians", distinguishes itself through their capacity to seamlessly integrate cutting-edge digital and design thinking skills with an unwavering dedication to client satisfaction. Brillio takes pride in its status as an employer of choice, consistently attracting the most exceptional and talented individuals due to its unwavering emphasis on contemporary, groundbreaking technologies, and exclusive digital projects. Brillio's relentless commitment to providing an exceptional experience to its Brillians and nurturing their full potential consistently garners them the Great Place to Work® certification year after year. Senior Lead AI/ML and Full Stack Engineer Primary Skills Writes production-grade code every day Builds systems, not POCs Owns deployment and operations Has strong software engineering fundamentals Agentic / Multi-Model Experience Azure + Copilot Stack Proficiency Secure AI /
Engineering Practices Specialization ML Engineering:
AI/ML Engineer Job requirements
Senior Lead AI/Full Stack Engineer Location:
Deerfield, FL Work Type:
Hybrid Model with min 2-3 days per week The mission Brillio is standing up this team because AI has collapsed attacker timelines from weeks to hours. You'll build the AI-native tooling that lets a small senior pod respond at machine speed, implementing work-focused security agents and the deterministic orchestration around them, wired into vulnerability-response stack (SIEM/SOAR/EDR, identity, vuln management, CMDB, ITSM).
This is a hands-on-keyboard seat:
you write production code, run agent fleets, and ship across the full SDLC. What you'll actually do Write production code. Repeatable work becomes compiled, testable binaries (Go-first); prompts drive persona behavior only. You build the tooling, not slideware about it. Operate agent fleets. Take a decomposed backlog, fan out parallel streams on conflict-free work, and bring it back through review gates. Build security in, not on. TDD test-writers ahead of coders, a dedicated validation stage (models hallucinate passing tests), persona judging against threat/security models, failures auto-looped as issues. Signed builds, SBOMs, and access control are table stakes. Integrate natively. Azure + GitHub Copilot, build-what's-missing in-stack. No third-party platforms, no AWS. Run model-agnostic. Personas across Claude / Copilot / ChatGPT because they fail differently; disagreement is signal. Manage token and context economics as an engineering constraint — just-in-time context loading, per-task budgets, alerts. Own your slice end to end. Design, develop, test, integrate, deploy, document, and KT — across the full SDLC. Must-have Senior engineer who still ships daily — hands-on-keyboard delivery, no exceptions. Deep Azure + GitHub Copilot delivery experience (primary stack, not a footnote). Strong Go (or equivalent systems language) for deterministic, testable orchestration tooling. Hands-on experience operating multi-agent / multi-model workflows in real delivery, not demos. Security-native instincts — TDD discipline, secure SDLC, threat modeling; comfort in a vulnerability-response context. Full-SDLC ownership of a work stream: design through deployment, docs, and knowledge transfer. Nice-to-have
SIEM / SOAR
/ EDR, identity, vuln-management, or
CMDB / ITSM
integration experience. Eval-harness, red-team, or agent-guardrail work (blast-radius sandboxing, reversibility, confidence thresholds, audit trails). Know what it's like to work and grow at
