The Principal, Applied AI Enablement role sits at the intersection of legal practice and applied AI — closer to an in-house R&D function than a traditional legal team role. This is a role for a tech-forward, innovative, engineer or product builder. You will identify where AI can do legal work that humans do today — or work humans simply cannot do at scale — prototype and ship AI tools and agents to handle it, and iterate with lawyers in the loop until those tools become a real part of how the function operates.
This role is about applying AI to the substance of legal work: the research, analysis, judgment calls, contract review, and regulatory tracking that lawyers do every day.
This is not a role about optimizing existing processes or rolling out off-the-shelf legal tech. It is a role about building things that didn't exist before — prototyping quickly, evaluating rigorously, and shipping the ones that work.
The role sits within Tinder Legal. You'll work with Tinder Legal leadership and team as your primary domain experts and end users, and partner with engineering, product, and other technical teams where deeper infrastructure is needed. Where capabilities you build prove valuable, there is potential to extend them more broadly — first to other Match Group Legal teams, and ultimately across the portfolio.
Spend time inside Tinder Legal and relevant Match Group Legal teams to understand how legal work happens today — product counseling, marketing reviews, contract review and negotiation, and regulatory compliance — with a focus on where AI can do meaningful legal work, not just where workflow improvements would help.
Develop a clear point of view on what AI is genuinely capable of in a legal context today, what's just around the corner, and where human lawyers should remain firmly in the loop.
Build the case for which opportunities are worth investing in and which aren't, based on impact, feasibility, and legal risk.
Design and build AI-powered tools — assistants, agents, retrieval systems, evaluators — that handle real legal work end-to-end or in close collaboration with legal team members.
Configure and orchestrate these tools across the data and systems they need to be useful (document repositories, knowledge bases, relevant internal sources), working within IT, Security, and Legal Ops-governed infrastructure — not around it.
Treat shipping as the starting line: measure quality against human baselines, debug edge cases, tune prompts and pipelines, and iterate as the underlying models and the business evolve.
Work directly with the legal team and end users to onboard them to new tools and workflows, gather feedback, and make those tools genuinely useful — not just technically functional.
Develop the documentation, examples, and attorney-facing training that helps legal team members understand both how to use AI tools and where their judgment must remain the decision-maker. These resources focus on substantive AI capability — how to use AI to do legal work better — and are distinct from Legal Ops resources on legal department systems and workflows.
Build evaluation harnesses and quality metrics — accuracy against human baselines, hallucination rates, coverage, latency — and use them to know when something is working and when it isn't.
Coordinate with Legal Operations, IT, Security, and Privacy when AI tools need to integrate with enterprise systems or comply with enterprise governance. Legal Ops, IT, and Security own those system layers, and anything that touches them requires their involvement.
Partner with Tinder Legal leadership to develop a forward-looking view of what an AI-native legal function could look like and what it will take to get there.
In collaboration with Legal Operations, track the state of the art in legal AI and applied AI more broadly — what frontier labs are shipping, what's emerging in legal-specific tooling and workflows, what other in-house teams are building — and translate it into what's worth experimenting with at Tinder.
As the pilot matures and capabilities prove themselves, help develop a roadmap for how successful tools and approaches could extend to other Match Group Legal teams.
Success in this role is about novel legal capabilities created and adopted — not process or operational metrics.
Number and quality of AI capabilities shipped: tools that the Tinder legal team actually use and rely on, not pilots that gather dust.
Speed and rigor of experimentation: how quickly and reliably the team can move from idea to evaluated prototype.
Categories of legal work meaningfully shifted from "humans only" to "AI-with-humans" or "AI-only."
Adoption of capabilities built within Tinder Legal, with early signals of readiness to extend to other Match Group Legal teams as the pilot matures.
Sustained quality: tools remain current, maintained, and performing as the underlying models and legal landscape evolve.
A builder at heart — you'd rather ship a rough prototype this week than write a perfect spec for one to be built next quarter.
Equally comfortable talking with lawyers about risk and with engineers about data models, APIs, and configuration trade-offs.
Hands-on experience with applied AI — prompting, agents, evaluations, RAG, fine-tuning — and a genuine curiosity about where models are headed.
Pragmatic and business-oriented: you care less about technical purity than about shipping things that genuinely improve what the legal team can do.
Comfortable with the fact that the underlying models, tools, and best practices will keep changing — and energized rather than frustrated by that.
Honest about what AI can and can't do today; you don't oversell AI to lawyers, and you don't undersell it to skeptics.
A curious and respectful change agent - you move fast and push for meaningful improvement, while taking time to understand existing frameworks, tooling, workflows, and stakeholder functions — bringing empathy and collaboration to applied AI.
4+ years of relevant experience building, deploying, or applying AI products and tools — at an AI-forward technology company, a startup, a law firm innovation team, or in-house.
Hands-on experience with modern AI techniques: prompting, agentic workflows, retrieval-augmented generation, evaluations, and the basics of fine-tuning or model selection.
Strong technical fluency: comfortable configuring platforms, working with APIs and data, and reasoning about integrations, permissions, and guardrails.
A track record of shipping — getting things into the hands of real users, learning from how they're used, and iterating.
Excellent communication and collaboration skills across legal, technical, and business audiences. You are a teacher and can bridge the gap between technical and plain language vocabulary.
Experience building AI products in regulated, compliance-sensitive, or high-stakes domains (legal, healthcare, financial services, trust & safety).
Experience in a "legal engineer," "legal AI engineer," "legal solutions architect," "legal technologist," or "applied AI engineer" role at a law firm, tech company, or AI lab.
Comfort with a pilot model: building something new within a defined team, measuring it rigorously, and helping make the case for broader rollout if it works.
AI is changing what's possible in legal practice on a timeline measured in months, not years. This role is our bet that the right way to capture that opportunity is to put a dedicated builder inside the legal team and have them ship.
For the right person, this is an unusually open mandate: real problems to solve, lawyers and leadership who want to lean into AI, and the freedom to define what an AI-native legal function actually looks like — starting at Tinder, with a clear path to broader impact if the pilot succeeds.
Based on 637 disclosed AI Engineering salaries on RoleSuite, the role pays a median of $201K/year, with most offers between $165K and $242K (10th–90th percentile: $132K–$285K).
This posting lists $150K–$220K, in line with the $201K market median.
See the full AI Engineering salary breakdown →