Presales Architect Team Lead

Description Presales Architect Team Lead

Location:

US / Canada (Eastern Time) - Home based Job Type: Full-time, Permanent About All Cloud

All Cloud is a leader in amplifying organizations’ cloud potential through AI. With a track record of hundreds of successful migrations and implementations across AWS and Salesforce, All Cloud has developed strategies and solutions that enable businesses of all sizes to remain at the forefront of innovation.

All Cloud is a leader in AI-led professional and managed services. As an AWS Premier and audited managed services Partner, and Salesforce Consulting partner, All Cloud provides comprehensive AI-led cloud journey support, from initial migration to ongoing management through our Engage Managed Services. Our expertise ensures that clients remain aligned with ecosystem best practices while focusing on their core business growth.

All Cloud serves clients across the globe with offices in EMEA and North America.(Use the "Apply for this Job" box below)..io

We are looking for a Presales Architect Team Lead to build, lead, and elevate our team of Presales Solutions Architects (PSAs) — a group spanning both cloud infrastructure and data & AI specializations. This is a player-coach role: you will lead the team while personally owning presales on our most strategic and complex opportunities.

Presales at All Cloud is where technology meets commercial strategy. Your team is the technical voice in front of the customer — running discovery, shaping the solution, and building the levels of effort (LOEs) and SMCs that become our proposals and SOWs. Done well, the architecture we propose is the reason we win. Done poorly, it is the reason we lose.

That is the bar for this role. We are looking for a leader who is as fluent in the commercial motion — deal structure, margin, funding programs, partner incentives, competitive positioning — as they are in AWS architecture. You will coach your architects to mature from being technical order-takers to becoming creative deal-shapers: people who listen for the customer's real business outcome, craft a solution that is technically sound and commercially compelling, and give the sales team something they can sell.

You will report to sales leadership and partner daily with Account Executives, Delivery, and our AWS partner team.

• Lead and mentor the PSA team:
  Manage a team of presales architects across infrastructure and data & AI specializations — setting standards, coaching on customer engagement, and growing each architect's technical and commercial range.
• Raise the quality bar:
  Own the review and approval of LOEs, SMCs, proposals, and solution designs before they reach the customer, ensuring accuracy, defensibility, and consistency across the team.
• Build the playbook:
  Create and maintain reusable assets (discovery frameworks, estimation models, solution blueprints, proposal templates, and objection-handling guides) so that quality does not depend on which architect is assigned.
• Capacity and coverage:
  Allocate architect coverage across the sales team, balancing workload against pipeline priority, deal size, and technical fit.
• Enablement:
  Run continuous enablement on new AWS services, All Cloud offerings, competitive landscape, and commercial and funding mechanics.

• Discovery and requirements:
  Set the standard for how the team uncovers requirements, constraints, success criteria, and decision drivers — asking the questions behind the question rather than accepting the stated ask at face value.
• Estimation:
  Own the LOE and SMC discipline end to end: scoping, assumptions, risk, phasing, and pricing inputs. Estimates must be credible to delivery and defensible to the customer.
• Thought leadership:
  Act as a trusted advisor who can articulate a customer's multi-year cloud, data, and AI journey — not just the next project. Represent All Cloud at webinars, workshops, customer briefings, and partner events.
• Cross-domain fluency:
  Guide opportunities that span infrastructure modernization, migration, and cost optimization as well as data platforms, analytics, and applied AI/GenAI.