Service Delivery Lead

Role Overview

The Service Delivery Lead (SDL) is the ultimate execution authority responsible for turning won software and services contracts into active, value-generating enterprise deployments. Embedded inside customer-facing strike Teams, this role transitions accounts from commercial sign-off through configuration execution to operations. The SDL leverages engineering-led rigor and advanced AI-driven automation to accelerate implementation and shrink time-to-value for strategic global clients. Post-deployment, the SDL manages the operations of the deployed SPM instance, ensuring active dialogue and value realization for the customer.

Key Responsibilities

Strategic Engagements & Pre-Sales Scoping

• Deployment Blueprinting & Planning:Partner with Sales and Product Owners in value workshops to map the 'Configure & Install' framework. Delineate technical paths and prepare implementation plans with effort estimates.
• Scope & Resource Management:Collaborate with SMEs to explicitly lock down engineering scope boundaries and delivery timelines. Optimize project team resourcing and prevent unnecessary feature creep to conserve developer bandwidth.
• PMO Coordination:Ensure cost and effort alignment within proposed commercial frameworks.

Account Deployment & Execution

• End-to-End Delivery Ownership:Securely manage and execute the entire Structural Performance Management (SPM) solution deployment lifecycle for strategic enterprise accounts.
• Project & Quality Control:Track baselines and milestones, manage financial fulfillment, and spearhead the resolution of onboarding friction. Partner with QA to ensure deployed instances pass UAT and engineering standards.
• Support Handover & Operations:Cleanly transition deployed solutions to Customer Enablement. Post-deployment, manage operations, monitor customer health, and animate Structural Digital Twin use cases.

AI Adoption & Delivery Acceleration

• Workflow Automation:Lead AI and Automation Strike Teams to systematically optimize blueprinting paths for primary heavy industry asset models (e.g., Piping, Pipelines, Cokers, Reactors, SMRs).
• Time-to-Value Optimization:Embed agentic capabilities and expand AI-assisted workflows into routine deployment procedures.

Requirements & Qualifications

• Professional Experience:5+ years leading complex engineering software deployments in B2B SaaS, Downstream/Upstream energy, or heavy industrial simulation.
• Project Management:Proven ability to negotiate across Sales, Product, and Backend Engineering validation gates to deliver on schedule. Agile expertise in handling deployment sprint cycles.
• Technical Rigor:Highly comfortable with complex engineering applications, technical engineering information, and cloud-based data integrations.
• Language Skills:Fluency in written and spoken Portugueseand Englishis mandatory. Spanish and other language skills are a plus.
• Automation Mindset:Demonstrated interest or experience leveraging AI copilots, agentic scripts, or automated frameworks to actively scale productivity.