Full-Time

Senior AI Identity Platform Engineer

LTS

LTS

201-500 employees

Builds, deploys, sustains mission-critical federal IT

No salary listed

Remote in USA

Remote

Bachelor's

Category
DevOps & Infrastructure (1)
Required Skills
Microsoft Azure
Python
LDAP
Java
TypeScript
Role-based Access Control
Microservices
SAML
AWS
Go
REST APIs
OAuth
Google Cloud Platform

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Requirements
  • 7+ years of software engineering, platform engineering, identity engineering, or cloud security experience.
  • Bachelor's degree in Computer Science, Software Engineering, Cybersecurity, Information Systems, or a related technical discipline (or equivalent professional experience).
  • Experience designing authentication and authorization architectures for enterprise applications.
  • Strong knowledge of OAuth 2.0, OpenID Connect (OIDC), JWT, SAML, PKI, and modern identity protocols.
  • Experience integrating enterprise identity providers such as Microsoft Entra ID, Okta, Active Directory, or similar IAM platforms.
  • Experience building secure REST APIs, microservices, and distributed systems.
  • Knowledge of Zero Trust Architecture, RBAC, ABAC, delegated authorization, and identity federation.
  • Experience with cloud platforms (Azure, AWS, or Google Cloud).
  • Strong programming skills in Python plus experience with Go, Java, or TypeScript.
  • Excellent communication, analytical, and problem-solving skills.
  • Experience designing secure systems that enable innovation rather than restrict it.
  • Expertise in identity and access management.
  • Hands-on experience with cloud-native architecture and modern authentication frameworks.
  • Strong ability to stay current with emerging AI technologies and evolving identity standards.
  • Ability to collaborate effectively across software engineering, security, and AI disciplines.
  • Willing and able to take ownership of difficult technical challenges and build elegant, innovative solutions.
Responsibilities
  • Design identity services supporting autonomous and multi-agent AI systems.
  • Establish secure identities for AI agents, enterprise services, users, and external integrations.
  • Define identity lifecycles for AI agents, including provisioning, credential management, rotation, and decommissioning.
  • Build reusable identity capabilities that scale across the AI platform.
  • Design and implement modern authentication and authorization frameworks for AI agents and platform services.
  • Implement OAuth 2.0, OpenID Connect (OIDC), JWT, service principals, mutual TLS (mTLS), and delegated authorization models.
  • Apply least-privilege and Zero Trust principles throughout AI workflows.
  • Build fine-grained authorization models controlling AI access to enterprise data, APIs, tools, and services.
  • Integrate AI platforms with enterprise identity providers such as Microsoft Entra ID, Okta, Active Directory, and other IAM solutions.
  • Enable secure identity federation across cloud and on-premises environments.
  • Design secure service-to-service authentication supporting distributed AI architectures.
  • Collaborate with enterprise security teams to align AI identity with organizational security standards.
  • Design secure frameworks governing how AI agents discover, authenticate to, and invoke enterprise APIs, databases, and external tools.
  • Build authorization models controlling agent capabilities and delegated permissions.
  • Protect sensitive enterprise resources through policy-driven access controls.
  • Implement secure credential handling and secrets management across AI workflows.
  • Develop reusable identity services, SDKs, APIs, and libraries supporting secure AI application development.
  • Automate identity provisioning, credential lifecycle management, and authorization policies.
  • Improve developer productivity through standardized identity services and secure engineering patterns.
  • Partner with platform engineers to integrate identity services into the AI platform architecture.
  • Ensure every AI action is authenticated, authorized, attributable, and auditable.
  • Implement identity-aware logging, traceability, and policy enforcement.
  • Support compliance and governance requirements for highly regulated environments.
  • Partner closely with AI Security Engineers to establish secure-by-design AI development practices.
Desired Qualifications
  • Experience developing AI platforms, Agentic AI systems, or Large Language Model (LLM) applications.
  • Experience securing Retrieval-Augmented Generation (RAG) systems and AI tool integrations.
  • Familiarity with Model Context Protocol (MCP) and secure AI tool invocation.
  • Experience with HashiCorp Vault, Azure Key Vault, AWS Secrets Manager, or similar secrets management platforms.
  • Experience implementing identity services in Kubernetes and cloud-native environments.
  • Experience with AI governance, Responsible AI, or AI platform security.
  • Familiarity with LangGraph, LangChain, CrewAI, Semantic Kernel, AutoGen, or similar AI orchestration frameworks.
  • Experience supporting Federal Government or healthcare environments.
  • Identity or cloud certifications such as Microsoft Identity and Access Administrator, CISSP, Security+, CCSP, or cloud security certifications are a plus.

LTS provides both consulting and hands-on implementation for mission-critical needs in government and health, including disaster response, healthcare kiosks, occupational health, and federal IT work. Its approach combines program management, systems integration, and operations support to design, build, deploy, and sustain infrastructure and programs in the field. The company differentiates itself with end-to-end delivery across the full project lifecycle for government and health contexts, backed by experience across federal, state, local, and tribal levels and an emphasis on regulatory and security requirements. Its goal is to turn plans into durable, operational programs that keep communities safe and healthy.

Company Size

201-500

Company Stage

N/A

Total Funding

N/A

Headquarters

Herndon, Virginia

Founded

2005

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Simplify Jobs

Simplify's Take

What believers are saying

  • Lindsay Goldberg grew LTS revenue and EBITDA over 150% from 2020 to 2025.
  • Fifteen acquisitions and all-50-state coverage give Velocity immediate national scale.
  • Rail, renewable diesel, and generator fueling deepen cross-sell into mission-critical customers.

What critics are saying

  • Wind Point merged LTS into Velocity Rail in July 2025, eliminating standalone independence.
  • Commodity fuel delivery faces margin pressure if customers insource fueling or switch distributors.
  • Integration across 18,000 customers and 30,000 sites risks service failures and churn.

What makes LTS unique

  • 1998-founded LTS became North America's largest mobile on-site refueling operator by 2025.
  • LTS serves trucking, rail, marine, and emergency power without branch depots.
  • Its truck-to-truck model and 1,200 specialized vehicles create dense route economics.

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Benefits

Remote Work Options

Flexible Work Hours

Company News

Benzinga
Jul 22nd, 2025
LTS Sold to Velocity Rail Solutions

Lindsay Goldberg has completed the sale of Liquid Tech Solutions (LTS) to Velocity Rail Solutions. Under Lindsay Goldberg's ownership since 2020, LTS grew revenue and EBITDA by over 150%, expanded to all 50 states, and executed 15 strategic acquisitions. The transaction terms were not disclosed. Financial advisors included Harris Williams, UBS Investment Bank, and Citizens Capital Markets & Advisory.