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1–2 jobs· newest first

Security Architect / Security Engineer
Zscaler · Remote, US
$165K–$235KRemote · Full-time · Senior
Lead AI/ML Engineer
UnitedHealth Group

+10K new in the last hour

Security Architect / Security Engineer

Zscaler · Posted May 12, 2026

Remote, United States
Remote
Full-time · Senior
$165K–$235K per year
7+ years

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We are looking for a Security Architect / Security Engineer to join our team. This is a Remote-USA role, reporting to the VP, Information Security Engineering in the Exposure Management & Security Operations department.

Compensation

Base Pay Range $164,500—$235,000 USD

Responsibilities

Build secure agent runtimes, reusable libraries, reference implementations, and validation pipelines for agentic AI applications and workflows
Implement secure agent patterns including planner/executor flows, tool routing, structured outputs, memory/state controls, and RAG trust boundaries
Design and implement security controls for cloud-native environments across AWS, Azure, and GCP, including IAM, workload protection, and logging
Partner with platform and engineering teams to embed secure-by-default cloud controls into shared services and developer workflows
Lead incident response, triage, and remediation workflows for cloud platforms and AI systems in partnership with SOC and engineering teams

Requirements

Nice to have: AI technologies
Nice to have: OWASP LLM Top 10
Nice to have: MITRE ATLAS
Nice to have: NIST AI RMF
Nice to have: red-team testing

Skills

Python TypeScript Node AWS Azure GCP IAM logging workload protection Kubernetes IaC SIEM SOAR EDR CSPM CNAPP agentic AI tool/function calling multi-step planning RAG memory/state management orchestration

Benefits

health plans
vacation
sick time
parental leave
retirement

See full job description

Lead AI/ML Engineer

UnitedHealth Group · Posted Nov 6, 2026

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Lead AI/ML Engineer

Responsibilities

Design, develop, and deploy AI-powered solutions to address complex business challenges with an emphasis on responsible use of AI
Build and deploy production LLM agents that automate detection, triage, and remediation of platform and application issues
Design and tune RAG pipelines over runbooks, incident history, logs, code, and internal documentation, including chunking strategy, embedding selection, vector store design, hybrid/semantic search, and reranking
Implement agent orchestration, including tool/function calling, multi-step planning, multi-agent handoffs, memory, and state management
Build supporting infrastructure and software layers for agents, including tool wrappers, guardrails, human-in-the-loop approval paths, and fallback behavior

Skills

Large Language Model (LLM) agents Retrieval-Augmented Generation (RAG) pipelines Machine learning engineering System observability Developer experience SRE InfoSec Platform teams AI solutions Orchestration Tool/function calling Multi-step planning Multi-agent handoffs Memory State management

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Model and prompt engineering

Model selection

Prompt and context optimization

Output structuring

Cost/latency tuning

Parameter-efficient techniques

Evaluation pipelines

Quality metrics

Security platforms

Model Context Protocol (MCP)

Enterprise-approved AI tools