AI Automation Engineer
- Hiring from
- United States
- Work type
- Remote
- Posted
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POSITION SUMMARY
TSi is hiring an AI Automation Engineer: an early-career, hands-on developer who has built AI agents and wants to grow in building them securely. This person helps design, build, and maintain AI agents and integrations for TSi's internal operations and for TSi clients.
This is a builder role, not an AI user role. Technology direction and cybersecurity are owned by the CTO and Senior Director of Technology. This developer builds within that framework and, with guidance from senior staff, writes agents that are secure and privacy-protective by design — least privilege, controlled data access, human approval where it matters, and full auditability.
Applicants must have personally built and deployed at least one AI agent using APIs, tool/function calling, or agent frameworks. During the interview process, you will be expected to demonstrate your work, discuss architectural decisions, and explain how you addressed security and privacy considerations.
Applicants who cannot provide a portfolio, repository, demo, or walkthrough of an AI agent they personally built will not be considered.
KEY RESPONSIBILITIES
AI Agent Development
- Build, test, and deploy AI agents that automate multi-step business workflows using tool calling, function calling, and the Model Context Protocol (MCP).
- Integrate agents with TSi business systems (e.g., NetSuite, ServiceNow, CPQ, Smartsheet) through APIs and secure connectors.
- Support the deployment of AI agents and applications to cloud environments (Azure, AWS, or Google Cloud), including configuring services, managing secrets, and monitoring performance.
- Maintain code in source control, participate in code review, write automated tests, and document deployments.
This position requires hands-on software development. Daily work includes writing Python and/or TypeScript code, integrating APIs, debugging issues, reviewing code, and deploying solutions. This is not a no-code or low-code AI role.
Secure Agent Engineering
- Scope every agent to least privilege: only the tools, data, and permissions the task requires.
- Build defenses against prompt injection, data exfiltration, insecure output handling, and excessive agent autonomy (per the OWASP Top 10 for LLM Applications).
- Require human-in-the-loop approval for high-impact actions (financial transactions, record changes, external communications).
- Manage API keys and credentials through approved secrets management; never hard-code secrets.
- Log agent actions, tool calls, and decisions to support auditing and incident investigation.
- Test agents for security issues before release, including basic red-teaming with guidance from senior staff; document risks and mitigations for review by the CTO and Senior Director of Technology.
Privacy by Design
- Minimize, mask, or redact employee and client PII before it reaches a model or third-party service.
- Follow TSi data classification policy on which data may be used with which models and vendors.
- Build with applicable privacy obligations in mind, including state privacy laws and biometric privacy laws (e.g., BIPA) for video and identity data.
Collaboration & Compliance
- Follow TSi cybersecurity and IT policies and escalate security concerns.
- Assist with AI vendor and tool evaluations by providing technical input.
- Write clear documentation and runbooks so agents can be supported and audited.
- Train end users on the agents you build.
REQUIRED QUALIFICATIONS
- Proof of work: Has built at least one working AI agent (personal, academic, or professional project). A portfolio, repository, or walkthrough is required.
- Familiarity with Git or equivalent version control. Please be prepared to share a repository (e.g., GitHub, GitLab) that shows your commit history on a personal, academic, or open-source project.
- 0–2 years of software development experience, including internships or substantial personal projects.
- Proficiency in TypeScript and/or Python; solid with REST APIs, JSON, webhooks, and SQL.
- Hands-on experience (professional or project-based) with a major model’s APIs (e.g., Anthropic, OpenAI, Azure OpenAI, AWS Bedrock, Google Vertex AI).
- Familiarity with agent frameworks and tooling such as the Claude Agent SDK, OpenAI Agents SDK, or equivalent.
- Working understanding of secure development practices for AI: prompt injection mitigation, least-privilege tool design, secrets management, input/output validation, and audit logging.
- Ability to explain technical decisions and risks.
PREFERRED QUALIFICATIONS
- Experience integrating with ServiceNow, NetSuite, or Microsoft 365 / Copilot.
- Experience with MCP servers/connectors.
- Experience with cloud deployment (Azure, AWS, or Google Cloud). This is a growth area we will help you develop.
CORE COMPETENCIES
- Builder: Focused on getting working agents into use, and learns quickly from feedback.
- Security mindset: Treats security and privacy as design requirements, not afterthoughts.
- Accountability: Works independently on well-scoped tasks in a remote environment, takes ownership of assigned work, and asks for help early.
- Communication: Explains complex topics in plain language; documents thoroughly.
