Lead Technical Consultant

Perficient•Town and Country, MO

7d•$100,000 - $145,000

About The Position

Perficient's Lead Technical Consultant serves as the technical lead on a delivery team, setting technical standards, reviewing and approving team output, and leading technical conversations with clients. The role leads delivery in small, AI-first teams, where AI-generated requirements, stories, configuration, tests, and documentation are reviewed, corrected, and approved by an accountable person. The position owns technical design and hands-on delivery for Marketing Cloud Engagement solutions, including journeys, automations, data extensions, content, contact models, AMPscript, and server-side JavaScript. It integrates Marketing Cloud Engagement with Salesforce Core and other data sources, validates segments and sends, tests journey paths, and owns deployments for the assigned scope. The consultant also supports emerging work involving Marketing Cloud Next and Data 360. The role configures AI tooling and team guidance, uses AI to generate and review delivery artifacts, verifies generated work against current platform documentation and real data, and mentors consultants in AI-assisted development and review. Success requires technical depth, client presence, techno-functional judgment, AI-native delivery practices, and the ability to learn new platforms quickly.

Requirements

6–9 years of relevant experience, including client-facing consulting.
Experience leading Salesforce technical delivery and builds on client engagements.
Marketing Cloud Engagement implementation experience, including journeys, automations, data extensions, and AMPscript.
Experience integrating Marketing Cloud Engagement with Salesforce Core.
Integration and data-model design experience.
Marketing Cloud Email Specialist certification.
Marketing Cloud Developer certification.
Demonstrated current use of AI tools in delivery and code review.
Strong written and spoken communication skills, including the ability to explain complex topics to technical and non-technical audiences.
Ability to connect technical decisions to business outcomes and explain trade-offs.
Ability to lead technical conversations with clients and communicate justified decisions, including saying no when appropriate.
Ability to configure team AI use and demonstrate corrections made to generated assessments.
Ability to deliver outside a primary cloud and quickly close knowledge gaps.

Nice To Haves

Marketing Cloud Consultant certification.
Exposure to Marketing Cloud Next or Data 360.
Production deployment accountability on a live client system.

Responsibilities

Own the technical design for a pod's scope, including the data model, security, integration approach, and build order.
Set and enforce technical standards, naming conventions, and branching strategy before development begins.
Review generated code and configuration, disposition findings as confirmed, corrected, or escalated, and remain accountable for missed issues.
Record technical approval on every story before it enters a sprint and correct inaccurate drafted technical assessments.
Verify platform capability claims against current documentation before sharing them with clients or incorporating them into designs.
Build hands-on, especially on the most challenging components, and stay close to the code to assess its quality.
Own deployments for the assigned scope, using a rehearsed runbook and a passed smoke test.
Mentor consultants on building with AI and reviewing AI-generated work.
Build Marketing Cloud Engagement journeys, automations, data extensions, content, and contact models.
Write and maintain AMPscript and server-side JavaScript as required by the solution.
Integrate Marketing Cloud Engagement with Salesforce Core and program data sources.
Validate segments and sends before execution.
Support the transition toward Marketing Cloud Next and Data 360 and learn these platforms as project work requires.
Write tests from acceptance criteria and verify every journey path in the environment.
Configure team AI tooling, including repository context, standards files, and instructions, to support work that meets engagement standards.
Use AI for first-pass review, then personally disposition each finding.
Generate journey logic, AMPscript, queries, and test data with AI and verify them against real data before use.
Use AI to document existing Marketing Cloud configuration before making changes.
Critically review generated work, correct it as needed, and be able to explain changes made before approval.
Work fluently with the AI tools available on an engagement, such as Claude, Microsoft Copilot, GitHub Copilot, platform assistants, or a client's own tools.
Lead technical conversations with client stakeholders and explain technical decisions and trade-offs to technical and non-technical audiences.