The bar
What you'll bring
- 8+ years in customer-facing technical delivery — implementation, engineering, professional services, technical program management, or product management with hands-on scope
- A demonstrated track record of shipping complex technical projects with external stakeholders, on a real deadline, with real consequences
- Strong communicator and coordinator: you can run a customer working session in the morning and drive internal alignment across three teams in the afternoon
- Product instincts — you naturally ask what problem this actually solves and what the smallest thing that solves it is
- Comfortable with ambiguity and partial information; you make progress before the picture is complete
- Bias toward automation and repeatability over heroics; you'd rather fix the process than run it manually again
- 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
Additional notes
Other
Altana is the network for trusted trade. Our AI-powered product network empowers governments and businesses to build a more resilient and secure global economy while keeping trade flowing.
The Opportunity at Altana
The Implementation team is the tip of the spear in getting Altana's platform into production inside our customers' businesses. We own the path from signed contract to realized value: standing up integrations, wiring Altana into the customer's existing business processes, and making sure the insight we deliver actually changes decisions on the customer's side.
We are a delivery organization with a technical core. We work directly with customer stakeholders — from trade compliance analysts to enterprise IT — and we work just as closely with Altana's engineering, data science, and product teams to translate what we learn in the field into what gets built next.
Design and deploy agentic AI systems
Design, build, and deploy agentic AI workflows — multi-step agents, tool and function calling, and automations — that power the customer's business processes and act on real customer data
Ground agents in customer context: connect them to the right data sources, APIs, and systems of record, and define the tools, permissions, and guardrails they operate within
Write and refine the prompts, system instructions, and evaluation criteria that make an agent reliable enough to trust in production
Build the orchestration and human-in-the-loop checkpoints that keep agentic workflows safe, auditable, and correctable in a customer's environment
Monitor, evaluate, and iterate on deployed processes — tracking accuracy, cost, and latency, and tuning them as the customer's data and needs evolve
Own technology implementation and delivery
Lead customer implementations end to end: scoping, configuration, integration, validation, go-live, and handoff to steady-state support
Configure and deploy Altana's platform capabilities against real customer data and real customer workflows, resolving the gap between what the product does today and what this customer needs
Build the connective tissue — API integrations, data handoffs, automations, and internal tooling — that makes an implementation work, using AI-assisted development to move quickly
Drive implementations to a definition of done that includes adoption, not just deployment: the customer's team is using it, in their process, without us in the room
Engage customers as a trusted technical partner
Serve as the primary technical point of contact through implementation — running working sessions, demos, or technical deep dives with stakeholders from analyst to executive
Elicit requirements from customers who often can't fully articulate them yet, and translate business problems into concrete technical scope
Communicate credibly in both directions: explain platform behavior, data quality realities, and trade-offs to non-technical audiences, and represent customer constraints faithfully back to Altana
Manage expectations, timelines, and scope with the directness that keeps large enterprise programs on track
Coordinate across internal teams
Orchestrate the internal effort behind each implementation, pulling in engineering, data science, product, and customer success at the right moments and keeping them aligned on a single plan
Escalate and unblock: identify what only another team can solve, make the ask precisely, and follow it to resolution
Feed field learning back into the product organization — patterns across customers, recurring friction, gaps worth building
Build reusable playbooks, templates, and documentation so the next implementation is faster than the last
Apply product management judgment
Own the implementation roadmap for your accounts: sequence work by customer value and delivery risk, and make explicit calls about what ships now versus later
Write clear requirements, specs, and acceptance criteria that engineering and data science can build against
Prioritize against customer value delivery timelines and cooperate with the product team on milestones and deadlines
Define what success looks like for each implementation in measurable terms, and track against it