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 Portuguese and English is 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.