Presales Solution Architect - Application Managed Services
Publicis Sapient · Posted Oct 13
Enterprise AI platforms, digital business transformation, software engineering, and strategy consulting services
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About the role
Publicis Sapient is a digital transformation partner that helps established organizations reach their digitally enabled state by fusing strategy, consulting and customer experience with agile engineering. The Application Managed Services (AMS) presales team shapes enterprise application maintenance and support deals, translating client application portfolios, support demand, and business priorities into deliverable service models, defensible cost estimates, and practical transformation roadmaps. This Presales Solution Architect role owns the solution across discovery, proposal development, client defence, and delivery handover, designing how AI, agentic workflows, automation, and reliability engineering improve service quality while working with cloud and infrastructure specialists on integrated pursuits.
What you will do
- Lead AMS pursuits from qualification and RFI/RFP analysis through solution reviews, final bid revisions, and delivery handover.
- Define scope, assumptions, exclusions, dependencies, and contractual responsibilities.
- Run discovery workshops and assess application portfolios, ticket history, business criticality, technical debt, release demand, existing SLAs, and current support costs.
- Identify gaps in client data and test the assumptions used in the bid.
- Design L1, L2, and L3 support responsibilities, service hours, on-call arrangements, escalation paths, and interfaces with business teams, service desk, product engineering, infrastructure, and vendors.
- Include maintenance, minor enhancements, and release support where contracted.
- Build bottom-up effort and staffing estimates using ticket volumes, handling effort, complexity, backlog, non-ticket activities, coverage constraints, utilization, and skill mix.
- Cross-check with application and benchmark sizing; estimate enhancements separately using story or effort-based methods.
- Shape commercial options with finance and sales, including managed capacity, fixed-price services, consumption-based models, and outcome-linked elements where measurable.
- Model transition costs, tooling, transformation investment, multi-year productivity, margin, and demand sensitivity.
- Define transition waves, knowledge transfer, shadow and reverse-shadow support, readiness criteria, staffing ramp-up, and service acceptance.
- Address incumbent dependencies and continuity risks before committing to the delivery plan.
- Develop AI-led AMS solutions for ticket classification and triage, retrieval from approved knowledge, incident investigation assistance, knowledge creation, and controlled runbook execution.
- Explain each workflow, integration, evaluation method, escalation route, and operational owner.
- Distinguish deterministic automation, AIOps, GenAI assistance, and agentic execution.
- Specify access controls, permitted actions, approval thresholds, audit trails, fallback, and rollback for actions that affect production.
- Quantify net benefits after platform, model, integration, and operating costs.
- Create a phased transformation roadmap covering recurring problem elimination, shift-left support, observability, SRE practices, test and release automation, and targeted modernization.
- Establish baselines and measurable outcomes without counting the same productivity benefit twice.
- Produce executive summaries, service architecture, operating models, staffing plans, pricing assumptions, transition plans, and value cases.
- Present and defend the solution to client business and technology leaders and respond to commercial and technical challenges.
- Coordinate sales, delivery, engineering, security, cloud, AI, finance, and partner teams.
- Obtain delivery validation of the staffing and transformation commitments, then transfer an agreed solution baseline to the delivery team.
- Build reusable estimation models, AMS reference architectures, proposal assets, and industry use cases; improve them using pursuit outcomes and delivery feedback.
Skills used in this role
What the employer is looking for
- 12 or more years of relevant IT experience, including at least 5 years in AMS presales or managed services solution architecture, with personal ownership of enterprise application support pursuits.
- Comparable experience is considered where the candidate can demonstrate the same depth.
- Demonstrable ownership of RFP responses, solution design, effort and FTE estimation, pricing inputs, client presentations, and delivery handover.
- Able to explain personal contribution, deal scale, assumptions, and the decisions made.
- Strong understanding of application support operations and ITIL practices, including incident, request, problem, change, knowledge, and service-level management.
- Experience designing global delivery, shared services, and support across time zones.
- Ability to build and challenge spreadsheet-based resource and cost models, distinguish workload from minimum coverage, and evaluate demand, effort, staffing, and savings scenarios.
- Working knowledge of enterprise application architecture and support dependencies across custom applications, integrations, databases, batch processing, and packaged platforms.
- Able to coordinate specialist teams across a mixed technology portfolio.
- Practical understanding of Agile, DevSecOps, observability, SRE, and application modernization sufficient to design an executable improvement roadmap and explain service and cost implications.
- Ability to design and cost an AI or agentic AMS use case, explain required data and ITSM integrations, define evaluation and production controls, and show a credible benefit case.
- Using AI only to draft proposals does not establish this capability.
- Strong client communication and workshop facilitation.
- Able to defend assumptions, negotiate scope trade-offs, and align senior stakeholders while leading several pursuits.
Preferred qualifications
- An implemented AMS automation, GenAI, or agentic workflow with evidence of service improvement, effort reduction, and operational adoption; experience moving from pilot to production.
- Experience with ticket analytics, application portfolio assessment, vendor consolidation, complex transitions, or large outsourcing deals.
- Experience integrating ITSM, observability, knowledge, and automation platforms, such as ServiceNow, Dynatrace, AppDynamics, Splunk, or equivalent tools.
- Familiarity with retrieval-augmented generation and tool or API orchestration.
- Exposure to cloud operations, FinOps, ERP or CRM support, digital commerce, or industry-specific applications.
- ITIL, cloud, or architecture certifications are advantageous.
Benefits and support
- Flexible work arrangements
- Generous paid time off
- Comprehensive health and wellness support
- Career development opportunities
About Publicis Sapient
Publicis Sapient is a digital business transformation company that helps organizations create and sustain competitive advantage through a blend of strategy, consulting, experience design, and engineering. Operating as a subsidiary of Publicis Groupe, the firm leverages proprietary enterprise AI platforms like Sapient Bodhi, Slingshot, and Sustain to modernize legacy systems and accelerate digital capabilities. With over 30 years of history, it partners with global enterprises across diverse industries to reinvent how they operate and serve their customers.
- Industry
- Digital Transformation
- Company size
- 20000+ employees
- Founded
- 1990
- Location
- Boston, Massachusetts, USA
- Funding stage
- Public Company
Funding
Public Company · $3.7B raised
- 2015-02-01Acquisition$3.7B
Leadership
Chief Executive Officer
Nathalie Le Bos
Chief Financial Officer
Chief Marketing Officer
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