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AI Enablement Engineer

Milestone Technologies, Inc.United States🇺🇸United States

Quick overview

Salary$90/hr

SeniorityMid Senior

Work modeRemote

LocationUnited States

WorkdayOAuthERPNetSuiteHRISLLMZendeskSalesforceCI/CD

Job description

Sr. AI Enablement Engineer/Hands-on
100% Remote = PST HOURS
Six+ Month W2 Contract
W2 ONLY - No Corp to Corp or 1099 support at this time. Applicants must be authorized to work in the U.S. without the need for STEM OPT, or any future visa sponsorship.
Rate: Approx. $90/hr./W2
Role Overview
We're seeking a Sr. AI Enablement Engineer to advise on, build, integrate, and operate AI
tooling for several departments within the client environment. You'll be the dedicated technical partner who
turns AI capability into real workflows that teams use every day, owning the connector and MCP
integrations that make those workflows possible, and work with cross-functional teams to
evaluate new technologies in this space that we are seeking to adopt.
This is a hands-on technical IC role inside BizTech (Business Technology), partnering closely
with teams across G&A, GTM, and Engineering. You'll spend your time evaluating vendors,
prototyping AI workflows for business processes, writing integration code, and shipping tools
that internal teams can extend on their own. The ideal candidate is a senior IC engineer who is
equally comfortable in a code review, a privacy lawyer's office hours, and a People Operations
workflow whiteboard — and who sees making other employees more productive with AI
as the actual job.
What You'll Do

Extend and govern AI workflows across the company. The client already runs AI agents in production, including automated IT support, with more functions coming online.
You'll extend that into People, Legal, Finance, and Workplace: partner with the team that owns each high-friction workflow, ship the AI-powered version, and make sure it's governed and measured.
Own technical governance of internal AI tools. Define the publishing process, scoping rules, and review cadence for the plugin and skill marketplace. Own the pre-deployment security-review path for new AI tools, and stand up spend and usage monitoring so cost and access stay visible as adoption scales.
Own the MCP and connector roadmap for enterprise systems. Several MCP integrations are already piloted against core systems. You'll harden those into production and scale the pattern across HRIS, ERP, contract management, ticketing, and knowledge bases — defining the roadmap, building the integrations, and communicating what's available.
Translate emerging AI capability into the clients' internal roadmap. Track new MCP servers, agent frameworks, and new agentic features across the platforms in use, and make a clear, opinionated call on what to adopt, ignore, or wait on for relevant use cases.
Run AI vendor security and privacy reviews as a structured workstream. AI-adjacent vendor evaluations land on BizTech regularly and are handled ad hoc today. You'll build a documented intake, a reusable AI vendor risk framework, and a clear sign-off path, partnering with Privacy, Security, and Legal.
Build integration prototypes and reference architectures. Ship working examples that internal teams can extend on their own, so you're not the bottleneck for every new workflow.
Be the technical partner of choice for G&A teams. Sit next to Finance on a NetSuite workflow, next to People on a Workday-flavored automation, next to Legal on a contract intake flow, and next to Privacy on a vendor review. Translate fluently in every direction.

What You Have:

5+ years of software or integration engineering experience, with at least 2 years building integrations between SaaS systems (HRIS, ERP, contract management, internal platforms, communication tools).
Hands-on experience with API integration patterns, OAuth and identity, webhook architectures, and the kind of glue work that makes enterprise systems actually talk to each other reliably.
Practical experience with LLM-based applications and AI tooling — prompt design, agent workflows, retrieval, evaluation, or production integration of model APIs. You don't need to have trained a model; you do need to have shipped something real that depends on one.
Working knowledge of the Model Context Protocol (MCP) or comparable agent-tool integration patterns. If you haven't shipped MCP yet, you've at minimum read the spec and built something against it.
Strong communication and stakeholder-management instincts, especially with non-technical partners — you can be the most technical person in a Privacy review and the most pragmatic person in an engineering one in the same afternoon, sitting between Finance, People, Legal, IT, and Privacy without losing context.
Strong DevOps and operational fundamentals — CI/CD, infrastructure-as-code, secrets management, and observability. You treat the integrations and AI tools you ship as production systems: version-controlled, monitored, and safe to change without breaking the teams that depend on them.
Demonstrated experience applying data governance & security best practices.
Demonstrated comfort evaluating third-party vendors — reading DPAs, reasoning about subprocessor chains, asking the right questions about data flows, and translating findings into clear go/no-go recommendations for the business.
Ability to thrive in a fast-paced, high-growth, and global environment with significant ambiguity.

Bonus Points:

Background that includes both a customer-facing role (Forward Deployed Engineer, Solutions Engineer, Applied AI Engineer) and an internal tooling role.
Familiarity with enterprise iPaaS platforms.
Experience inside a Business Technology, IT, or internal platform org at a high-growth B2B SaaS company.
Hands-on work with enterprise platforms like NetSuite, Workday, Ironclad, Zendesk, Salesforce, etc, including their APIs, custom development, or AI-adjacent extensions