Staff AI Engineer

Securitas Security Services•Elmsford, NY

13h•$155,000 - $180,000•Hybrid

About The Position

Securitas is seeking a Staff AI Engineer to lead hands-on development of its enterprise Intelligence platform, which hosts agents and APIs powering mobile and web applications. The role drives the architecture of the AI ecosystem, integrates third-party vendor agents, and mentors engineers across internal and external teams. The engineer will develop an Agentic AI platform in a cloud-native Azure environment, with emphasis on zero-trust security, scalability, and performance. They will design reusable agent templates and orchestration workflows, establish Bring Your Own Agent (BYOA) standards, build automated testing and CI/CD release workflows, and support integrations with third-party enterprise systems. The role also involves guiding engineers and contractor teams, enforcing AI security practices, and using GenAI and developer automation tools to improve workflows. The position is hybrid (two days per week) for candidates within commuting distance, or fully remote. Minimal travel is required, up to two domestic trips per year. The annual pay range is $155,000–$180,000. Actual compensation depends on experience, qualifications, work location, applicable laws, and business needs.

Requirements

At least 8 years of software engineering experience.
Deep proficiency in Python and modern API development.
Proven success designing, deploying, and observing LLM-powered applications.
Experience orchestrating multi-agent workflows using LangGraph and building scalable RAG systems.
Hands-on experience with cloud-native Azure architectures, such as Azure AI Foundry, Container Apps, Cosmos DB, and Key Vault.
Experience building robust API integrations, external system connectors, or MCP and A2A connectors.
Strong understanding of AI observability tools such as Langfuse for tracking latency, token usage, control-flow decisions, and session analytics.
Track record of shipping high-impact features quickly while managing technical debt pragmatically.
Technical initiative and willingness to propose new solutions and architectures.
Low-ego collaboration and eagerness to adapt initial designs based on team feedback.

Responsibilities

Lead hands-on development of the Agentic AI platform in a cloud-native Azure environment, prioritizing zero-trust security, scalability, and performance.
Build and deploy agents that connect with third-party enterprise vendors, such as workforce management and HR platforms.
Design secure, reusable agent templates, orchestration workflows, and Model Context Protocol (MCP) and Agent 2 Agent (A2A) connectors.
Establish Bring Your Own Agent (BYOA) standards and automated testing and CI/CD release workflows with QA and DevOps.
Guide and code-review internal engineers and contractor teams, maintaining technical excellence and enforcing AI security best practices.
Use GenAI and developer automation tools to optimize workflows and speed execution.
Proactively propose solutions and architectures, and adapt designs based on team feedback.