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Altana is an AI-powered platform for trusted trade, helping governments and businesses build 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 insights drive actual business decisions.
As Senior Manager of Delivery, you will lead and grow a team of AI Deployment Engineers responsible for customer implementations across a portfolio of accounts. You own the full delivery lifecycle: hiring and developing engineers, managing team capacity and staffing, establishing operating rhythms (planning, reviews, retrospectives), and building a culture of ownership and adoption-focused delivery where success means customers use the system independently.
You will own delivery outcomes across every account your team touches—from agentic AI in production to adoption metrics and measurable business impact. You set and defend implementation roadmaps, sequencing by customer value and delivery risk, and define success metrics for each engagement. You step into the hardest implementations yourself when they require senior technical judgment or customer relationship management.
You will set the technical bar for agentic deployment across your team: defining standards for designing, deploying, and operating agentic AI systems (prompts, evaluations, tool integrations, guardrails, orchestration, human-in-the-loop controls). You review and raise quality across reliability, safety, auditability, cost, and latency in real customer environments, staying hands-on enough to review team work and unblock deep technical problems.
You serve as the senior technical relationship owner across your accounts—from analysts to executives—translating ambiguous business problems into agentic solutions and setting realistic expectations on timeline, scope, and AI capabilities. You represent customer constraints faithfully back to Altana and platform realities credibly back to customers.
You orchestrate engineering, data science, product, and customer success teams behind your implementations, keeping everyone aligned. You escalate and unblock precisely, identifying what only other teams can solve and owning it to resolution. You feed field learning back into the product organization—patterns across customers, recurring friction, and platform gaps.
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 every level—coach engineers, run executive conversations, drive internal alignment across multiple teams
- Product and portfolio instincts—prioritize across competing demands and say no with defensible rationale
- Comfortable with ambiguity and accountable for outcomes before the picture is complete
- Bias toward automation, standards, and repeatability over heroics
TECHNICAL COMPETENCIES:
- Hands-on depth to set the bar: built or deployed agentic AI systems yourself (LLM-powered agents, tool/function calling, retrieval-augmented generation, 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, 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 hold credible conversations with 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: 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.
