Software Product Management Pre Sales Senior Manager - Supply Chain

Accenture•Miami, FL

4d•$122,700 - $271,000

About The Position

Accenture is hiring a Senior Manager, Pre-Sales to support complex enterprise software sales cycles for its Supply Chain OS (SCOS). The role combines product and supply chain expertise with client-facing communication to advance opportunities through demonstrations, technical and functional responses, solution scoping, proposals, proof-of-concept support, partner enablement, and industry events. The successful candidate will explain and demonstrate SCOS’s AI-native foundations, including ontologies, knowledge graphs, and semantics, and show how these support auditable and improvable supply chain decisions. They will demonstrate the platform across realistic supply chain scenarios, scope AI proof of concepts, design and present deployment architectures, assess data readiness, discuss SAP IBP integration and migration, and engage stakeholders across IT, architecture, supply chain, and data governance. The position requires at least eight years of relevant enterprise software pre-sales, solution consulting, or technical sales support experience; at least eight years of experience with enterprise software delivery models and integrations; and at least 12 months supporting pre-sales for AI-native software. A bachelor’s degree or equivalent experience is required. Travel may be required at a rate of 0–80%, depending on client and business needs. Compensation varies by location, role, skills, and experience. The posting is anticipated to remain open until November 28, 2026.

Requirements

At least 8 years of pre-sales, solution consulting, or technical sales support experience in enterprise software.
Track record contributing to complex sales opportunities, including RFP responses and solution demonstrations.
At least 8 years of experience with enterprise software delivery models, including SaaS, license, and managed services, and integration approaches.
At least 12 months of demonstrated pre-sales experience supporting AI-native software products built on LLMs, agentic workflows, or machine learning platforms, with evidence of delivered demonstrations or RFP contributions.
Bachelor’s degree or equivalent, with a minimum of 12 years of work experience; alternatively, an associate’s degree with a minimum of 6 years of work experience.
Experience presenting technical solutions to mid-level and C-suite stakeholders.
Strong written and verbal communication skills, including the ability to produce high-quality proposal content under time pressure.
Organized and detail-oriented, with the ability to manage multiple concurrent opportunities.
Self-motivated and resilient, with the ability to thrive in a fast-paced environment.
Deep functional understanding of AI-native architecture, including ontologies, knowledge graphs, semantics, and how these support enterprise-grade agent decision-making.
Functional knowledge of supply chain planning and operations, including demand sensing and forecasting, inventory optimization, supply planning, procurement orchestration, logistics management, supplier collaboration, and control towers.
Ability to demonstrate SCOS through realistic, end-to-end supply chain scenarios and tailor demonstrations to industry and buyer needs.
Ability to scope supply chain AI proof-of-concept engagements and present results to supply chain and finance evaluators.
Ability to design and present SCOS deployment architectures and explain their business value to technical and executive audiences.
Understanding of supply chain data requirements, data quality remediation, and data readiness assessments.
Familiarity with SAP IBP integration patterns, coexistence or replacement approaches, data synchronization, and transition planning.
Understanding of supply chain planning methods, including statistical forecasting, machine-learning demand sensing, multi-echelon inventory optimization, constraint-based scheduling, and S&OP.
Familiarity with agentic supply chain design, including goal definition, tool use, constraint handling, and human-in-the-loop approval design.
Ability to navigate multi-stakeholder technical evaluations and communicate appropriately with IT leaders, architects, supply chain teams, and data governance leaders.

Nice To Haves

AI certifications such as Microsoft AI-900 or AI-102, Google Cloud Professional ML Engineer, AWS Certified Machine Learning Specialty, or DeepLearning.AI specializations.

Responsibilities

Support the end-to-end pre-sales process for assigned opportunities, including discovery, product demonstrations, RFP responses, solution scoping, and proposal preparation.
Deliver tailored product demonstrations to mid-level and senior client stakeholders, translating product features into business value.
Facilitate client workshops to identify requirements, validate fit, and shape solution approaches.
Prepare RFP, RFI, and security questionnaire responses in coordination with product, legal, and delivery teams.
Support proof-of-concept engagements, document outcomes, and feed learnings into the pre-sales playbook.
Support channel and technology partners through demonstrations, technical guidance, solution positioning, and assistance with partner-led opportunities.
Represent the business at industry events and trade shows by demonstrating products, engaging prospects and clients, and recording leads and follow-up actions.
Develop and maintain reusable pre-sales materials, including demo scripts, solution blueprints, proposal modules, competitive battle cards, and ROI templates.
Stay current on product updates, competitors, and industry trends, and share insights with the sales team.
Contribute to onboarding new team members on product and solution knowledge.
Work with the sales lead and AD Pre-Sales to align opportunity strategy and solution approach.
Maintain accurate records of pre-sales activities and solution configurations, and support pipeline reporting as needed.
Participate in win/loss reviews and apply findings to improve proposal quality and demonstration effectiveness.
Demonstrate SCOS’s AI-native foundations, supply chain functionality, and end-to-end scenarios; handle live questions and adapt demonstrations to buyer needs.
Scope supply chain AI proof-of-concept engagements, including product families, planning horizons, forecast model configuration, retrospective accuracy testing, and results presentations.
Design and present SCOS deployment architecture, including integrations with ERP, WMS, TMS, supplier portals, IoT sensors, and financial planning systems.
Assess supply chain data requirements and readiness, including data quality remediation needs.
Address SAP IBP integration, coexistence or replacement, synchronization design, and transition planning.
Engage technical and business stakeholders at the appropriate level, including IT leadership, enterprise architects, supply chain systems owners, supply chain teams, and CDOs.