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Altana is an AI-powered platform for trusted global trade, helping governments and businesses build resilient and secure supply chains. The Implementation team owns the end-to-end delivery path from contract signature to realized customer value.
In this Staff-level role, you will design, build, and deploy agentic AI systems that power customer business processes. You'll ground AI agents in customer context by connecting them to data sources, APIs, and systems of record, then define the tools, permissions, and guardrails they operate within. You'll write and refine prompts, system instructions, and evaluation criteria to make agents reliable in production, and build orchestration and human-in-the-loop checkpoints that keep workflows safe, auditable, and correctable.
You'll lead customer implementations end to end—scoping, configuration, integration, validation, go-live, and handoff to steady-state support. You'll configure Altana's platform against real customer data and workflows, resolving gaps between product capabilities and customer needs. You'll build the connective tissue (API integrations, data handoffs, automations, internal tooling) that makes implementations work, using AI-assisted development to move quickly. Success means the customer's team is using the system in their process without your involvement.
You'll serve as the primary technical point of contact through implementation, running working sessions and technical deep dives with stakeholders from analysts to executives. You'll elicit requirements from customers who can't fully articulate them yet, translate business problems into technical scope, and communicate credibly in both directions—explaining platform behavior and trade-offs to non-technical audiences while representing customer constraints back to Altana.
You'll orchestrate internal effort across engineering, data science, product, and customer success, escalate blockers, and feed field learning back into the product organization. You'll build reusable playbooks, templates, and documentation to accelerate future implementations.
You'll apply product management judgment to own implementation roadmaps for your accounts, sequence work by customer value and delivery risk, write clear requirements and acceptance criteria, and define success in measurable terms.
The role is based in Amsterdam with flexibility to travel onsite to customer locations.
REQUIREMENTS:
- 8+ years in customer-facing technical delivery (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 on real deadlines with real consequences
- Strong communicator and coordinator; ability to run customer working sessions and drive internal cross-team alignment
- Product instincts; natural inclination to ask what problem something solves and what the smallest solution is
- Comfortable with ambiguity and partial information; ability to make progress before the full picture is clear
- Bias toward automation and repeatability over heroics
- Working proficiency in Python or comparable language; ability to read codebases, write and debug scripts, build integrations, and ship small features
- Fluency with SQL and comfort exploring and validating data independently
- Practical experience with AI-assisted coding tools (Claude Code, Cursor, Copilot, or similar) as a core part of daily work
- Hands-on experience building or deploying agentic AI systems (LLM-powered agents, tool and function calling, retrieval-augmented generation, multi-agent orchestration)
- Skill in prompt engineering and agent evaluation; ability to design prompts and evals, diagnose agent failures, and iterate toward reliable production behavior
- Familiarity with agent frameworks and protocols (MCP, LangChain, or similar) and wiring agents to external tools, APIs, and data sources
- Familiarity with APIs (REST, Swagger/OpenAPI), Git-based workflows, and cloud-hosted systems
- Enough understanding of data pipelines, data modeling, and ML systems to scope work, diagnose issues, and hold credible conversations with engineers
NICE TO HAVE:
- Experience with global trade, supply chain, customs, or trade compliance
- Background in enterprise software implementation at scale (multi-stakeholder, multi-quarter programs)
- Exposure to Spark, Databricks, or large-scale data processing
- Experience building internal tooling or automation that a team adopted
- Formal product management experience (roadmaps, specs, stakeholder prioritization)
