Socure
AI Enablement Engineer
Hub - New York · Senior
Sponsorship not specifiedDetected 43 days ago
Code ReviewPlatform EngineeringJiraConfluenceCadenceLeadershipCommunication
Stay score
odds of building a lasting career here
37Risky
Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70
Thin sponsorship signal and lottery-bound. A low-probability bet with your clock running. Prioritize cap-exempt roles and proven entry-level sponsors first.
Lottery odds assume a STEM candidate.
Personalize to your clock →Employer immigration record
from this employer's Department of Labor filings
Green-card filing pattern in this occupation
Context, not a finding about this posting: of this employer's 4 green-card filings in this occupation, 100% were for a worker who already held the job.
Files H-1B transfers
3 transfer filings in the last year, covering 3 workers. Median labor-condition decision: 10 days. An employer that already files transfers is one that can take over an existing H-1B.
Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.
Community outcomes
No reports yet — be the first to help the next applicant.
About the role
- We are looking for an AI Enablement Engineer to accelerate AI adoption across engineering by turning standards, tooling patterns, and proven workflows into repeatable day-to-day practice.
- This role sits at the intersection of AI tooling enablement, developer productivity, engineering standards, lightweight training, feedback loops, and technical storytelling.
- You will serve as the connective tissue between the leaders defining AI foundations and standards and the broader engineering organization that needs to adopt them.
Responsibilities
- Drive AI adoption and standardization across engineering
- Serve as the primary enablement partner for AI foundations, standards, and framework adoption across the engineering organization.
- Reinforce practical adoption through examples, short demos, applied workflows, and direct support rather than relying only on broad show-and-tell sessions.
- Own the feedback loop and continuous improvement motion
- Build and maintain a structured feedback loop with the engineering community to understand what is working, where friction exists, and which standards or workflows need refinement.
- Coordinate continuous improvement of AI standards and frameworks, not just their rollout, by channeling field feedback back to the leaders building them.
- Create mechanisms to gather lightweight input from engineers, team leads, and managers on adoption blockers, tooling gaps, and workflow quality.
- Create lightweight, high-frequency enablement content
- Create concise do and do not guides, examples of strong AI-assisted workflows, review checklists, and quick-reference materials that reinforce expected engineering behaviors.
- Build repeatable prompt patterns, templates, and content-generation workflows that can be reused by engineering leaders and the broader org.
Requirements
- 5+ years of experience in developer productivity, developer experience, technical enablement, engineering communications, technical program leadership, or a similar role in a fast-moving technical organization.
- Strong understanding of how modern engineering teams work, including software development lifecycles, code review, testing, developer tooling, platform/reliability concepts, and adoption of engineering standards.
- Ability to turn evolving technical standards into clear, practical, high-frequency enablement for engineers and managers.
- Strong written and verbal communication skills, with the ability to translate complex technical ideas into concise, useful guidance for different audiences.
- Comfort partnering across engineering leadership, platform teams, operations, recruiting, and business stakeholders.
- Strong experience using AI tools like Claude, ChatGPT, Gamma, Cursor, and related platforms to create content, package workflows, summarize information, and build reusable assets quickly from existing source material.
- Demonstrated ability to create reusable AI-assisted workflows, including prompt libraries, short-form enablement content, templates, and playbooks.
- Experience building feedback loops, adoption mechanisms, or learning systems that help organizations change behavior at scale.
- High ownership, strong judgment, attention to detail, and bias for action in ambiguous environments
Nice to have
- Experience in B2B SaaS, platform engineering, identity/fraud/risk, fintech, or other technically complex environments.
- Familiarity with engineering productivity metrics, usage analytics, cost governance, or dashboarding related to AI tooling.
- Experience running office hours, technical communities, guilds, brown bags, or other structured enablement programs.
- Familiarity with tools such as Notion, Confluence, Slack, Jira, Glean, LearnUpon, Jellyfish, or knowledge automation systems.
- Experience creating executive-ready materials from raw technical inputs.
- Socure is moving quickly toward a more agent-enabled engineering model, but adoption is still uneven and too reliant on a small number of power users.
- Without dedicated enablement, strong standards can remain disconnected from daily engineering behavior.
- This role closes that gap by helping the org adopt, improve, and operationalize AI standards in a way that is practical, measurable, and durable
Benefits
- Support onboarding and engineering learning where it matters
- Support role-specific learning where needed, but keep the primary focus on AI adoption and engineering enablement rather than owning onboarding as the central charter.
Company info
- ABOUT THE ROLE We are looking for an AI Enablement Engineer to accelerate AI adoption across engineering by turning standards, tooling patterns, and proven workflows into repeatable day-to-day practice.
- Partner with leaders across platform, engineering, and operations to identify where AI should become part of default engineering practice rather than an optional side project.
This listing is sourced directly from Socure's careers page and normalized into a canonical job model.