Jobs at Perficient

Leads content strategy for an enterprise digital transformation and CMS migration program. Responsibilities include content audits, information architecture, taxonomy, metadata and content modeling, governance, migration and redirect planning, localization workflows, SEO/AEO/GEO optimization, and AI-enabled content operations. The consultant facilitates senior stakeholder workshops, advises clients, coordinates the content workstream, contributes to Agile requirements and delivery, and mentors team members while partnering with design, engineering, analytics, and platform teams.

Lead the architecture and implementation of enterprise-scale Azure data and AI platforms, including data lakes, lakehouses, warehouses, integrations, machine learning, and generative AI solutions. Establish governance, security, MLOps, and AI frameworks; guide cloud modernization, migration, performance, and cost optimization. Translate business needs into technical architectures, present recommendations to executives, lead architecture reviews, support client pursuits, and mentor engineering teams.

Lead the architecture, implementation, integration, and optimization of Oracle EPM Planning solutions. Design planning, budgeting, forecasting, modeling, security, metadata, and reporting frameworks; configure Oracle EPM modules; and apply AI-driven forecasting capabilities. Lead requirements workshops, testing, deployment, stakeholder presentations, and pre-sales activities. Mentor consultants and developers while advising finance and executive stakeholders on enterprise planning transformation initiatives.

Designs, develops, tests, and deploys AI and machine learning applications, including generative AI, LLM, RAG, and AI agent solutions. Builds scalable training and inference pipelines, integrates models through APIs and microservices, works with structured and unstructured data, and monitors system performance, reliability, and security. Collaborates with data scientists, engineers, product managers, and business stakeholders while applying cloud, MLOps, and emerging AI technologies.

Design, execute, and maintain automated tests for web, API, and application platforms. Perform manual and regression testing, analyze results, manage defects, conduct root cause analysis, and report quality metrics. Serve as a client-facing QA representative, participate in Agile ceremonies, collaborate with cross-functional teams, and recommend improvements to automation frameworks and testing processes.

Lead data architecture pursuits and complex client engagements, including workshops, requirements analysis, future-state architecture, implementation roadmaps, platform integration, and proof-of-concept development. Communicate complex solutions to technical and executive audiences, lead globally distributed teams, modernize legacy architectures, and provide thought leadership across data management, governance, modeling, cloud, and analytics technologies.

Architects enterprise digital commerce transformations using Adobe Commerce Cloud, Adobe Commerce Optimizer, App Builder, API Mesh, and AI technologies. Designs composable, headless, agentic, and SaaS-modernized commerce ecosystems; guides migrations from monolithic or PaaS architectures; develops integration patterns for AI search, recommendations, support, inventory, and pricing; and establishes governance for secure, ethical AI adoption. The role also uses AI and LLM tools for system modeling, architecture blueprints, code and API audits, data-flow mapping, and legacy modernization strategies.

Architect Adobe Commerce extensions, serverless infrastructure, AI microservices, agents, and API Mesh integrations. Establish AI-assisted coding, testing, review, security, and coding standards across engineering teams. Optimize Core Web Vitals, edge caching, GraphQL performance, and secure upgrade-safe App Builder implementations. Build proof-of-concepts for AI agents, checkout experiences, and edge functionality. Serve as the technical authority for Adobe Commerce out-of-process extensibility and performance engineering.

Acts as the bridge between business stakeholders and technical teams on Adobe Commerce projects. Leads requirements discovery for B2B and B2C commerce, translates needs into epics, user stories, process maps, specifications, and acceptance criteria, and maps requirements to Adobe Commerce capabilities. Manages and prioritizes backlogs in Jira or Azure DevOps, supports Agile ceremonies, defines UAT scenarios, and advises on AI-driven personalization, search, recommendations, segmentation, and merchandising.

Define and lead ServiceNow architecture and target-state roadmaps, ensure best-practice scalable implementations, design integrations and CMDB/CSDM strategies, provide technical leadership across delivery, support AI-enabled ServiceNow capabilities, and collaborate with stakeholders to ensure platform sustainability and governance.

Provides architectural leadership for MuleSoft and enterprise integration initiatives. Defines API-led connectivity strategies, security frameworks, governance standards, roadmaps, and reusable integration patterns. Designs integrations across Salesforce, ERP, data platforms, warehouses, and cloud applications, including event-driven architectures. Leads architecture reviews, proofs of concept, technical discovery, Agile solution design, and delivery support. Oversees observability, monitoring, CI/CD, and operational excellence while mentoring technical teams and managing stakeholder dependencies, risks, and integration challenges.

Leads end-to-end Salesforce data migration and integration initiatives. Designs ETL processes, writes SQL and SOQL queries, develops automation scripts, performs data profiling and transformation, resolves migration issues, and ensures data quality, security, governance, reconciliation, and cutover readiness. Collaborates with Salesforce, integration, and business teams while documenting repeatable migration procedures and leveraging AI tools.

Lead iOS architecture and deliver native Swift/SwiftUI features for a regulated financial client. Own modularization, state management, CI/CD, testing, secure data handling, API integration, and App Store releases. Mentor a mid-level engineer and enforce compliance and quality standards while leveraging AI-assisted tooling to accelerate delivery.

Lead product vision, define roadmaps, write user stories, prioritize backlogs, and accept sprint deliverables. Collaborate with stakeholders, clinical and pharmacy teams, and engineering to deliver Medicare and MTM-focused healthcare solutions while leveraging AI and data to improve outcomes and compliance.

The Director of Organizational Change Management leads enterprise change initiatives, develops strategies to ensure adoption, and partners with executives to drive transformation.

Lead architecture and hands-on development for Twilio-based contact center solutions. Design roadmaps, build POCs, mentor teams, support Agile delivery, liaise with stakeholders and offshore teams, and drive technical strategy and implementations using React/Node.js and AWS.

Design and lead scalable Salesforce Sales Cloud solutions, scope projects, advise clients as a trusted technical lead, guide and QA consultant work, manage risks, and leverage AI tools (Einstein/Agentforce) to improve sales processes across pipeline, forecasting, and opportunity management.

Lead technical consultant responsible for full software development lifecycle: estimating, design, implementation, testing, deployment, and support. Serve as technical lead and mentor, translate requirements into technical designs, collaborate with architects and developers, and communicate solutions to technical and non-technical stakeholders.

Lead Data Scientist will develop, validate, deploy, and monitor predictive ML models, design scalable data pipelines, perform advanced SQL analysis, partner with stakeholders to translate business needs into production-ready solutions, and contribute to data science best practices and governance.

Lead data scientist responsible for developing, validating, deploying, and monitoring predictive ML models; building scalable data pipelines; performing advanced SQL-based ETL and analysis; partnering with stakeholders to translate business needs into production-ready ML solutions; and contributing to best practices for modeling, governance, and MLOps.