Solution Consultant, Consumer Brands

Accelerize360 (A360) is an AI-enabled consulting and technology firm that designs, builds, and runs applications, data, integration, and AI solutions for consumer-focused companies.

Our Consumer Brands practice serves mid-market to enterprise retail, CPG, apparel, beauty, footwear, and direct-to-consumer businesses, typically $500M–$5B in revenue. These organizations face enterprise-level complexity across multi-channel commerce, fulfillment, customer care, wholesale, and DTC operations, but often lack the budget, timeline, or internal resources for traditional multi-year transformations. Specialization and speed are central to how we serve this market.

A360 is also an Anthropic partner. Generative AI is embedded throughout how we discover, design, build, test, and support solutions and is a condition of employment on this team.
The Forward Deployed Engineering Model

A360 delivery is reorganizing around Forward Deployed Engineering: one integrated team with continuous accountability rather than separate consulting and technology handoffs. The person shaping the solution remains accountable for whether it works in production.
Role Overview

The Solution Consultant II is an independent workstream owner responsible for a defined scope from discovery and design through build, integration, testing, deployment readiness, handoff, and hypercare.

You are the client-facing owner of your workstream: you lead sessions, make defensible design decisions within engagement guardrails, review associate engineer output, manage dependencies, and protect delivery quality.

A commercially capable Solution Consultant II may lead a clearly bounded single-workstream implementation or defined managed services scope end to end, with delivery governance in place and an L3 available as escalation support.

Key characteristics

• Ownership: Own a defined workstream from requirements through hypercare, including quality and deployment readiness.
• Consumer domain: Apply expertise across customer care/contact center, commerce, order management and fulfillment, store/POS, and customer data.
• AI-native delivery: Use GenAI throughout delivery and evaluate whether AI-generated output is actually production-ready.
• Platform agnostic: Learn new platforms quickly and select the right mix of application, data, integration, automation, and AI. Salesforce experience is welcome but not required.

• Own requirements, success criteria, solution design, build/configuration, integration, testing, deployment readiness, documentation, handoff, and hypercare.
• Build and demonstrate rapid POCs using tools such as ClaudeCode to support discovery and pre-sales and generate new opportunities.
• Maintain an executable workstream plan covering estimates, milestones, dependencies, acceptance criteria, risks, and decisions.
• Translate business and technical requirements into working solutions, escalating decisions only when they exceed workstream authority or create material engagement risk.
• Manage requirement changes, scope pressure, competing priorities, and the critical path.
• Lead bounded POCs and prototypes, objectively validate results against agreed criteria, and document cost, risk, and scope implications before moving to build.
• Own deployment readiness, including runbooks, cutover, rollback, observability, support transition, documentation, and hypercare closure.

• Lead discovery, design, working sessions, and demonstrations for your workstream.
• Serve as the primary client contact for status, decisions, trade-offs, dependencies, and risks.
• Explain technical options in business terms, connecting decisions to outcomes, cost, timeline, security, and maintainability.
• Navigate difficult conversations involving expectations, ambiguity, or scope using facts, preparation, and appropriate escalation.
• Partner with Change Management/Program or Project Management on stakeholder readiness, adoption, training, and benefits; partner with Advisory when strategic outcomes or executive expectations shift.

• Make defensible architecture and design decisions within engagement standards and clearly explain trade-offs.
• Review associate engineer output before client exposure and ensure requirements, testing, documentation, security, and deployment standards are met.
• Own the workstream test strategy and evidence across functional, regression, integration, data, performance, security, and AI evaluation as applicable.
• Design for operational reality, including data handling, error paths, monitoring, support ownership, adoption, and maintainability.
• Diagnose delivery and technical issues, coordinate resolution, and document reusable lessons.

GenAI capability is a requirement of this role, not an enhancement.

• Use approved AI capabilities to accelerate discovery synthesis, solution design, engineering, testing, documentation, and analysis.
• Design and build GenAI solutions where they create measurable value, including retrieval/knowledge grounding, summarization, classification/routing, agentic workflows, and conversational interfaces.
• Select AI-assisted workflows based on quality, security, privacy, cost, latency, reliability, and client policy.
• Establish review and validation practices for AI-generated output and define evaluation criteria before build.
• Coach associate engineers in responsible AI use.
• Understand the difference between a demo and production system and clearly identify what is required to close that gap.
• Follow A360 and client data-use rules without exception. Never enter client data into unapproved tools or ship unvalidated AI output.

• Apply working knowledge of customer care/contact centers, B2B/B2C commerce, order management and fulfillment, store/POS, loyalty, and customer data.
• Understand relevant business drivers, including peak seasonality, unit economics, customer lifetime value, and cost of service versus revenue impact.
• Translate retail, CPG, and brand-side business needs into system requirements without requiring clients to speak technically.
• Apply patterns and lessons from prior consumer engagements rather than starting from scratch.

• Break work into clear assignments for associate engineers with context and acceptance criteria.
• Coach team members through pairing, reviews, demonstrations, and retrospectives.
• Maintain quality standards when an L3 is not present.
• Contribute reusable templates, reference architectures, accelerators, prompts, evaluations, and implementation patterns to A360 knowledge repositories.

• Understand how staffing, sequencing, rework, and timeline decisions affect margin and client value.
• Contribute estimates, assumptions, dependencies, risks, and technical content to SOWs, change requests, and project plans.
• Learn new concepts, domains, and technologies very quickly.
• Identify legitimate client growth opportunities or adjacent needs and route them to Client Development, Advisory, Sales, or Delivery leaders with a clear business case.
• Think beyond the current deliverable toward adoption, expansion, future phases, and reusable value.

• 6+ years in delivery-facing consulting, engineering, or product roles, including 3+ years in a client-facing consulting/professional services environment.
• Demonstrated success independently owning a bounded technical workstream on a live client engagement from requirements through deployment.
• Strong hands-on capability in at least one technical domain and working breadth across at least two of: application/platform configuration, custom development, cloud, data engineering, integration/APIs, automation, or quality engineering.
• Demonstrated GenAI capability in both how you work and what you build.
• Technology-agnostic mindset with the ability to quickly learn new platforms, frameworks, and tools.
• Ability to facilitate discovery, translate requirements, design solutions, estimate work, and manage delivery through go-live and handoff.
• Experience reviewing others' work and providing direct, constructive coaching and quality guidance.
• Strong client-facing communication skills, including the ability to explain technical trade-offs to both business executives and technical engineers.
• Working knowledge of professional services economics, including scope control, change control, utilization, and margin.
• Sound judgment regarding security, data handling, responsible AI, and production readiness.

• Consumer vertical experience: Retail, CPG, apparel, beauty, footwear, specialty, or DTC.
• Salesforce: Service Cloud, Sales Cloud, Commerce, Order Management, Data Cloud, or Agentforce. Useful but not required.
• Contact center: CCaaS, cloud telephony migration, omnichannel routing, knowledge management, or AI agents.
• Commerce & order management: B2B/B2C commerce, OMS, fulfillment, and ERP integrations such as SAP, AS400, or NetSuite.
• Agentic AI: Agent design, orchestration frameworks, tool use, and evaluation/testing of AI systems in production.
• Data platforms: Snowflake, Databricks, dbt, or comparable technologies, including hands-on pipeline experience.
• Presales: Experience participating in client conversations and contributing to estimates or SOWs.
• Practice building: Experience contributing an accelerator, offering, standard, or capability beyond an individual engagement.