AI Operations Lead
Listed on 2026-07-03
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Software Development
AI Engineer (Applied/Software)
About the Role
Taktile builds AI products for the world's most complex decisions and we hold ourselves to the same standard internally. We believe the companies that win the next decade will be the ones that turn AI from a tool into a multiplier - embedded into how every team works.
We're looking for an AI Enablement Lead to make this the reality s is a high-leverage, internal-facing operations role: you won't be building features for our customers, you'll be building the tools, integrations, and workflows that make every Taktilian faster and better at their job.
You will be the first hire dedicated to this mission, working closely with team leads across the company to identify, build, and scale the AI workflows with the biggest impact. You will take over a program that was set up internally and comes with support for infrastructure and agent-building. You will operate at both strategic and hands-on levels: setting the roadmap and reporting directly to leadership, while also building workflows and running enablement yourself.
Taktile is a hybrid company. This role requires working at least 3 days per week from one of our offices in Berlin, Iasi, or London.
What You'll Do Strategy & Roadmap- Define and own Taktile's internal AI roadmap, prioritize use cases across Go-to-market, Operations, and G&A
- Track market trends, peer practices, regulatory evolution, and emerging tools — stay on the frontier, know when new tools and models release, which ones are worth experimenting with, and bring the best back into the business
- Continuously evaluate and improve our setup to maximize adoption and improve efficiency of our teams
- Report to leadership on progress, AI adoption, and program ROI
- Set the internal standard for "production-ready" AI workflows and act as the escalation point and quality bar for everything our teams ship
- Define a build vs. buy framework for AI point solutions – assessing, approving, or deprecating tools in close collaboration with our teams
- Build internal tools and agents end-to-end that wire Taktile's SaaS stack (Hub Spot, Notion, Linear, Gong) into our engineers' and operators' daily workflows. Own scope, design, implementation, rollout, and iteration.
- Evolve AI architecture based on internal customer needs and tangible, measurable improvements.
- Identify, prioritize, and scale automation opportunities across business units, while clearly differentiating what can and should be automated and to what degree vs. what should not (yet)
- Find the highest-leverage workflows. Embed with teams across Engineering, GTM, Customer Success, Finance, and Operations to identify where AI can remove the most friction.
- Build team-level ownership and coordinate a network of AI champions so workflows are maintained without central dependency
- Drive adoption, not just deployment. Run hands‑on workshops, pair sessions, and office hours to teach teams how to actually use what you ship. Measure success in real adoption and time saved, not features delivered.
- Partner with Security and IT on governance. Apply least‑privilege principles from day one. Build the guardrails, access scoping, and audit trails that let us move fast on AI without exposing customer data or production systems.
- 5+ years in consulting, operations, or a similar cross‑functional senior role
- Ability to write and review production‑grade Python and SQL – preferably with a strong technical background – e.g., Data Science
- Technical deployment experience + hands‑on experience building with modern LLM tooling – agent frameworks, tool use, prompt engineering, MCP, evals
- Enough technical depth to converse about LLM pipelines, agentic workflows, and integrations
- Excellence breaking down complex problems and making quick, well‑informed decisions even under pressure
- Strong program management skills across complex, multi‑stakeholder environments
- Fluent English, both written and spoken. Strong written and verbal communication skills from leadership reporting to internal playbooks – with both technical and non‑technical operators alike
- AI:
Claude - Programming Language:
Python - Data Platform: AWS,…
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