Senior Manager of Delivery, Altana

• 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
• A track record of building and growing high-performing technical teams that ship complex work for external stakeholders, on real deadlines, with real consequences
• A player-coach mindset: you lead the team and can still go deep technically when it matters
• Strong communicator and coordinator at every altitude — you can coach an engineer, run an executive conversation, and drive internal alignment across three teams in the same day
• Product and portfolio instincts — you prioritize across competing demands and say no, or “not yet,” with a defensible rationale
• Comfortable with ambiguity and accountable for outcomes before the picture is complete
• Bias toward automation, standards, and repeatability over heroics
• Enough hands-on depth to set the bar: you’ve built or deployed agentic AI systems yourself — LLM-powered agents, tool and function calling, retrieval-augmented generation, or multi-agent orchestration — and can review what your team produces
• Fluency in prompt engineering and agent evaluation, and the judgment to know when an agentic system is reliable enough for production
• Working proficiency in Python or a comparable language, and comfort with SQL, APIs (REST, Swagger/OpenAPI), Git-based workflows, and cloud-hosted systems
• Practical experience with AI-assisted coding tools (Claude Code, Cursor, Copilot, or similar) and with agent frameworks and protocols (MCP, LangChain, or similar)
• Enough understanding of data pipelines, data modeling, and ML systems to scope work, diagnose issues, and hold a credible conversation with the engineers who build them

Desirable

• The AI Deployment 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, deploying agentic AI 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
• This role leads that team
• Lead and grow a team of AI Deployment Engineers:
• Hire, coach, and grow a team of AI Deployment Engineers — set expectations, give direct feedback, and develop careers
• Own team capacity and staffing across a portfolio of customer implementations, matching engineers to accounts by skill, delivery risk, and development goals
• Establish the team’s operating rhythm — planning, reviews, and retrospectives that keep multiple implementations on track at once
• Build a culture of ownership, technical rigor, and adoption-focused delivery, where “done” means the customer is using it in their process, without us in the room
• Create the conditions for the team to move fast safely: shared playbooks, reusable tooling, and clear standards for deploying agentic systems in production
• Own the mission across your portfolio:
• Own delivery outcomes across every account your team touches: agentic AI in production, adoption, and changing decisions on the customer's side
• Set and defend the roadmap across implementations — sequencing by customer value and delivery risk, and making explicit calls about what ships now versus later
• Define what success looks like for each engagement in measurable terms, and hold the team accountable to it
• Step into the hardest implementations yourself when they need senior technical judgment or a steady hand with the customer
• Set the technical bar for agentic deployment:
• Define the team’s standards for designing, deploying, and operating agentic AI systems — prompts, evaluations, tool integrations, guardrails, orchestration, and human-in-the-loop controls
• Review and raise the quality of agent designs and deployments across reliability, safety, auditability, cost, and latency in real customer environments
• Stay hands-on enough to review what the team ships, unblock deep technical problems, and hold a credible conversation with Altana’s engineering and data science teams
• Codify what works into repeatable patterns so each deployment is faster and safer than the last
• Engage customers as a senior technical partner:
• Serve as the senior technical relationship owner across your accounts — from analyst to executive — and the escalation point when implementations get hard
• Translate ambiguous business problems into agentic solutions, and set realistic expectations on timeline, scope, and what AI can and can’t do reliably today
• Represent customer constraints faithfully back to Altana, and platform and data-quality realities credibly back to the customer
• Coordinate across internal teams:
• Orchestrate engineering, data science, product, and customer success behind your team’s implementations, keeping everyone aligned on a single plan
• Escalate and unblock precisely: identify what only another team can solve, make the ask, and own it to resolution
• Feed field learning back into the product organization — patterns across customers, recurring friction, and gaps worth building into the platform
• Technologies in Our Environment:
• Languages: Python, SQL, Spark
• AI tooling: Claude Code and other AI-assisted development tools, used daily
• Agentic AI: LLM agents, tool and function calling, MCP, retrieval-augmented generation, and agent orchestration frameworks
• Platform & infrastructure: Docker, Git, Kubernetes, Swagger/OpenAPI, AWS, Azure
• Datastores: Databricks, Elasticsearch, Postgres, Redshift