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At TaxDome, we’re building the #1 practice management platform for accounting firms in the US and globally. Founded in 2017, we’ve grown into a 400+ fully remote team across 40+ countries, serving tens of thousands of businesses worldwide with millions of end clients.
You’ll be part of a globally distributed team built on trust, ownership, and self-management.
We focus on outcomes over activity — prioritizing clear ownership, pragmatic decision-making, and accountability for results over rigid processes. Collaboration is central to how we operate: we communicate openly, involve the right people early, and continuously improve how we build products and teams together.
We're looking for a Senior AI Engineer to help us scale faster by designing and running production AI services - RAG-powered assistants, MCP servers, AI agents - and building smart automations for our teams. You'll choose the right tool for each problem, from Python services to low-code platforms like n8n, designing solutions that save time and boost efficiency.
This is a hands-on senior role: you'll own solutions end to end - from scoping a business problem and choosing the architecture, to building and integrating it, to shipping it securely and operating it. The role is as much about engineering judgment - deciding what to build, why, and with which trade-offs - as about building itself.
It's a fully remote role, we are hiring across the EU, with a preference for candidates working within CET (±3 hours).
Lead discussions on business challenges and propose solutions using LLMs, AI agents, custom services, or low-code tools - whichever fits best.
Make and document architecture and tooling decisions: code vs low-code, build vs buy, model selection - with explicit cost, latency, security, and maintainability trade-offs.
Design, build, and operate production Python services - including our retrieval-grounded assistant with RAG, database, auth, and CI.
Build and tune RAG pipelines: embeddings, vector search, and retrieval quality evaluation.
Design, build, and maintain MCP (Model Context Protocol) servers that connect internal tools, data sources, and APIs to LLMs and AI agents.
Design, configure, and maintain AI agents for internal projects - including tool-calling, orchestration, and multi-step agentic workflows.
Build and maintain automations in n8n.
Design, test, and optimize prompts and multi-step prompt chains, including systematic evaluation (evals) of prompt and pipeline quality.
Optimize cost and performance of AI workloads: caching, latency profiling, choosing the right model per task, token budgeting, basic load testing.
Use AI coding agents as a primary implementation tool: decompose problems into well-specified tasks, review and validate generated code, and keep the bar on tests, security, and maintainability.
Integrate external and internal services through REST APIs, webhooks, and OAuth flows.
Build internal MVP tools on top of generative models to validate business hypotheses.
Research, evaluate, and implement new automation and AI tools; run pilot projects with generative models.
Maintain a structured prompt and workflow library, and document solutions for maintainability and handoff.
Apply sound data-handling and security practices when working with internal systems, customer data, and credentials.
Collaborate cross-functionally to understand needs and deliver impactful, reliable solutions.
Example project: building a feedback hub that collects and processes user feedback from multiple sources (CRM, surveys, forums, call recordings) into a single dashboard.
5+ years in IT overall, including 2+ years hands-on building applications, agents, and automations on top of LLMs - applying generative AI to real products and business tasks — and demonstrated seniority owning solutions end to end.
Python - solid backend engineering: designing services, working with databases and APIs, writing tests, comfortable with Git, containers, and CI/CD. Not just scripting or extending existing automations.
Hands-on experience with RAG and retrieval: embeddings, vector databases, tuning retrieval quality.
Databases: SQL (Postgres) and key-value (Redis); familiarity with vector search (pgvector or similar).
Experience building and operating AI agents and agentic workflows (tool-calling, orchestration); solid understanding of LLM principles, AI workflow design, and multi-step prompt chains.
Demonstrated ability to justify technical decisions and reason about trade-offs (cost, latency, security, complexity) - not just implement what's asked.
Experience with AI-assisted development workflows (Claude Code or similar); able to stay accountable for the quality of agent-generated code.
Sound data-handling and security awareness (credentials, tokens, PII, access scopes).
Self-driven, curious, and proactive in experimenting with new tools and technologies.
English - Fluent: able to lead professional communication, handle correspondence, and participate fully in work meetings in English.
Experience designing and building MCP servers (otherwise we expect a fast ramp on MCP).
Experience with workflow automation platforms (n8n, Make, or similar).
Experience integrating OpenAI, Anthropic, or other AI APIs.
Experience integrating third-party services (Jira, Slack, Google, HubSpot, etc.) via REST APIs, webhooks, and OAuth flows.
Experience with LLM observability and eval tooling (Langfuse, promptfoo, or similar).
Experience running services on managed container PaaS platforms.
Background in text/data processing.
Experience with Google Workspace API, Slack API, CRM systems.
Familiarity with data/security governance frameworks relevant to internal tooling.
First 90 days: ramp on our stack (n8n, Python services, Postgres/pgvector, Redis, our PaaS), ship one meaningful automation or AI tool into production, document it, and make at least one documented architecture decision (e.g., code vs low-code for a real task).
First 6-12 months: own a portfolio of live automations, agents, and MCP integrations; establish reusable patterns and a well-maintained prompt/workflow library; measurably reduce manual effort across the teams you support and demonstrably optimize the cost/latency of at least one AI workload.
At TaxDome, we aim to create an environment where people can do their best work and grow alongside the company.
Competitive compensation, paid in USD, transparently shared before the first interview
Fully remote work with flexible hours
30 paid days off annually, plus sick days as needed
Health & well-being support
Learning & development budget to support your professional growth
English lessons reimbursement
Co-working space reimbursement
Company-provided equipment (conditions may vary depending on the role)
A high level of autonomy and ownership in your work
The opportunity to make a real impact in a fast-growing global SaaS company
A collaborative, international team with a strong product mindset
Upon successful completion of the interview process and acceptance of the offer to join, an employment verification check will be conducted as part of pre-boarding — confirming job titles and dates of engagement with 2 of your previous employers. This is a required step for all new joiners.
If you’re excited about this opportunity and believe you could make an impact at TaxDome, we’d love to hear from you!
Published on: 8/13/2026
TaxDome
We are creating a SaaS-platform that helps our customers to grow their business around the world. Our platform allows small and medium-sized businesses dealing with taxes, finance and accounting, to automate workflows.
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