Staff AI Deployment Engineer, Amsterdam

About the job

Responsibilities

• Design, build, and deploy agentic AI workflows, including multi-step agents, tool/function calling, and automations, to power customer business processes using real data.
• Connect agents to customer data sources, APIs, and systems of record, defining their tools, permissions, and guardrails.
• Write and refine prompts, system instructions, and evaluation criteria to ensure agent reliability in production.
• Build orchestration and human-in-the-loop checkpoints for safety, auditability, and correctability of agentic workflows.
• Monitor, evaluate, and iterate on deployed processes, tracking accuracy, cost, and latency, and tuning them based on evolving customer needs.
• Lead customer implementations end-to-end, including scoping, configuration, integration, validation, go-live, and support handoff.
• Configure and deploy Altana's platform capabilities against customer data and workflows, bridging gaps between product capabilities and customer needs.
• Build necessary integrations, data handoffs, automations, and internal tooling using AI-assisted development.
• Drive customer adoption of implemented solutions, ensuring teams use them within their processes without ongoing external support.
• Serve as the primary technical point of contact for customers during implementation, conducting working sessions, demos, and technical deep dives.
• Elicit and translate customer business problems into concrete technical scope, even when requirements are not fully articulated.
• Communicate technical platform behavior, data realities, and trade-offs to non-technical audiences, and represent customer constraints back to Altana.
• Manage customer expectations, timelines, and scope for large enterprise programs.
• Coordinate internal efforts across engineering, data science, product, and customer success teams for each implementation.
• Identify, escalate, and resolve technical blockers by collaborating with other internal teams.
• Feed field learnings, customer patterns, and friction points back into the product organization.
• Develop reusable playbooks, templates, and documentation to improve implementation efficiency.
• Own the implementation roadmap for accounts, prioritizing work based on customer value and delivery risk.
• Write clear requirements, specifications, and acceptance criteria for engineering and data science teams.
• Prioritize implementation tasks against customer value delivery timelines and cooperate with the product team on milestones.
• Define and track measurable success criteria for each implementation.

Requirements

• 8+ years in customer-facing technical delivery roles (implementation, engineering, professional services, technical program management, or product management with hands-on scope).
• Demonstrated track record of shipping complex technical projects with external stakeholders under deadlines.
• Strong communication and coordination skills, capable of running customer sessions and driving internal alignment.
• Product instincts, with an ability to identify the core problem and the smallest solution.
• Comfort with ambiguity and partial information, with a bias for making progress.
• Bias toward automation and repeatability over manual processes.
• Working proficiency in Python or a comparable language for scripting, debugging, building integrations, and shipping small features.
• Fluency with SQL for data exploration and validation.
• Practical experience with AI-assisted coding tools (e.g., Claude Code, Cursor, Copilot) for faster development and prototyping.
• Hands-on experience building or deploying agentic AI systems (LLM-powered agents, RAG, multi-agent orchestration).
• Skill in prompt engineering and agent evaluation, including designing prompts and evaluation criteria.