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Altana is building the network for trusted trade using AI-powered technology to help governments and businesses create a more resilient and secure global economy. The AI Deployment team is responsible for taking Altana's platform from signed contract to realized customer value—standing up integrations, deploying agentic AI into customer business processes, and ensuring the insights delivered actually change customer decisions.
As Senior Manager of Delivery, you will lead and grow a team of AI Deployment Engineers who work directly with customer stakeholders (trade compliance analysts, enterprise IT) and closely with Altana's engineering, data science, and product teams. This is a player-coach role combining people leadership with hands-on technical depth.
Key responsibilities include:
**Team Leadership & Growth**
- Hire, coach, and develop a team of AI Deployment Engineers; set expectations, provide feedback, and grow careers
- Own team capacity and staffing across a portfolio of customer implementations, matching engineers by skill, delivery risk, and development goals
- Establish operating rhythm through planning, reviews, and retrospectives to keep multiple implementations on track
- Build a culture of ownership, technical rigor, and adoption-focused delivery where "done" means the customer uses it independently
- Create conditions for fast, safe movement: shared playbooks, reusable tooling, and clear standards for deploying agentic systems in production
**Portfolio & Mission Ownership**
- Own delivery outcomes across every account your team touches: agentic AI in production, adoption, and measurable customer impact
- Set and defend implementation roadmaps, sequencing by customer value and delivery risk
- Define success metrics for each engagement and hold the team accountable
- Step into the hardest implementations yourself when they need senior technical judgment or customer relationship management
**Technical Leadership**
- Define team standards for designing, deploying, and operating agentic AI systems (prompts, evaluations, tool integrations, guardrails, orchestration, human-in-the-loop controls)
- Review and raise quality of agent designs across reliability, safety, auditability, cost, and latency in real customer environments
- Stay hands-on enough to review team work, unblock deep technical problems, and credibly engage with engineering and data science teams
- Codify patterns into repeatable processes so each deployment is faster and safer
**Customer & Internal Engagement**
- Serve as senior technical relationship owner across accounts (analyst to executive level) and escalation point for difficult implementations
- Translate ambiguous business problems into agentic solutions; set realistic expectations on timeline, scope, and AI capabilities
- Represent customer constraints faithfully to Altana and platform realities credibly to customers
- Orchestrate engineering, data science, product, and customer success teams behind implementations
- Feed field learning back to product organization—patterns, friction points, platform gaps
The role is based in Amsterdam with flexibility to travel to customer locations.
**Requirements**
- 8+ years in customer-facing technical delivery, including 2+ years leading engineers or technical delivery teams (implementation, solutions/forward-deployed engineering, professional services, technical program management, or engineering management)
- Track record building and growing high-performing technical teams that ship complex work for external stakeholders on real deadlines with real consequences
- Player-coach mindset: lead the team and go deep technically when it matters
- Strong communicator and coordinator at all levels—coach engineers, run executive conversations, drive internal alignment across teams
- Product and portfolio instincts; prioritize competing demands and say no with defensible rationale
- Comfortable with ambiguity and accountable for outcomes before the full picture is clear
- Bias toward automation, standards, and repeatability over heroics
**Technical Competencies**
- Hands-on depth in agentic AI systems: you've built or deployed LLM-powered agents, tool/function calling, retrieval-augmented generation, or multi-agent orchestration, and can review team work
- Fluency in prompt engineering and agent evaluation; judgment to know when agentic systems are production-ready
- Working proficiency in Python or comparable language; comfort with SQL, APIs (REST, Swagger/OpenAPI), Git workflows, and cloud-hosted systems
- Practical experience with AI-assisted coding tools (Claude Code, Cursor, Copilot, or similar) and agent frameworks/protocols (MCP, LangChain, or similar)
- Understanding of data pipelines, data modeling, and ML systems to scope work, diagnose issues, and credibly engage data engineers
**Nice to Have**
- Experience with global trade, supply chain, customs, or trade compliance
- Experience scaling delivery, professional services, or forward-deployed engineering teams
- Background in enterprise software implementation at scale (multi-stakeholder, multi-quarter programs)
- Formal product management experience (roadmaps, specs, stakeholder prioritization)
**Technologies in Environment**: Python, SQL, Spark, Claude Code and AI-assisted development tools, LLM agents, MCP, retrieval-augmented generation, agent orchestration, Docker, Git, Kubernetes, Swagger/OpenAPI, AWS, Azure, Databricks, Elasticsearch, Postgres, Redshift.
