Application Architect, IT - Architects

Application Architect, Enterprise AI ProgramPosition SummaryAs an Application Architect in the Enterprise AI Program, you will provide technical direction, architectural oversight, and hands-on engineering leadership across scrum teams building production AI-enabled software.This role sits between enterprise/program architecture and delivery teams, helping translate business needs and platform strategy into practical, scalable, secure, and maintainable technical solutions.This is a senior technical leadership role for someone who can:Shape architecture and implementation patternsGuide teams building AI-enabled applications, agents, workflows, and integrationsValidate technical direction through code, demos, and proofs of conceptEstablish reusable patterns, templates, and reference implementationsStay close to the codebase through code reviews, technical spikes, troubleshooting, and situational code contributionsEvaluate emerging AI technologies and educate the team through practical examplesThis role is not a full-time feature development position, but it is also not a hands-off architecture role. The Application Architect is expected to remain technically close to the platform and contribute directly when architectural complexity, delivery risk, production issues, or emerging platform patterns require senior technical involvement.You will help lead architecture across:Enterprise AI platform capabilitiesLLM-powered agents and agent workflowsRetrieval-augmented generation, or RAG, patternsModel Context Protocol-style tool integrationsDurable workflow and orchestration patternsInternal and external AI-enabled applicationsSecure integrations with Salesforce and internal Ascensus systemsObservability, evaluation, testing, and production support patternsAI-assisted engineering practices using tools such as Cursor, Claude Code, or similar platformsWe are looking for an architect who is practical, hands-on, delivery-oriented, and deeply curious about where AI engineering is headed. You should be able to set direction without creating unnecessary complexity, mentor engineers without becoming a bottleneck, and turn emerging technology into working examples that help teams move faster with confidence.What We’re Looking ForWe are looking for a technical leader who can:Translate business needs into practical AI platform architecture.Provide technical direction across multiple scrum teams.Align implementation decisions with enterprise architecture and platform strategy.Guide teams building agents, RAG pipelines, workflows, tools, integrations, and AI-enabled applications.Establish reusable patterns, templates, reference implementations, and engineering standards.Review designs and coach teams toward secure, scalable, observable, and maintainable solutions.Stay actively connected to the codebase through code reviews, technical spikes, POCs, reference implementations, troubleshooting, and situational code contributions.Evaluate emerging AI tools, models, frameworks, orchestration patterns, and development practices.Translate technical exploration into practical guidance, demos, reusable examples, and implementation standards.Help teams resolve technical impediments and production issues.Promote consistency and reuse across teams without slowing delivery.Communicate clearly with technical and non-technical stakeholders.Required Qualifications8+ years of professional software engineering experience.2+ years in a technical lead, application architect, solution architect, staff engineer, or comparable technical leadership role.Bachelor’s degree in Computer Science, Computer Information Systems, Business Information Systems, a related technical field, or equivalent practical experience.Strong experience designing, building, and supporting production software in medium to large business environments.Demonstrated ability to remain hands-on with the codebase through code reviews, proof-of-concept development, technical spikes, complex troubleshooting, and direct code contributions.Experience building proofs of concept, reference implementations, technical demos, templates, or reusable engineering patterns.Strong experience with modern software engineering practices, including:Clean codeSource controlCI/CDAutomated testingDesign patternsRefactoringAPI designObservabilityProduction supportStrong experience with one or more modern programming languages and platforms, such as:PythonJavaScript / TypeScriptSQLSimilar modern development platformsExperience designing distributed systems, service integrations, APIs, workflow logic, or platform capabilities.Experience with LLM-powered systems or AI-enabled applications, such as:RAGChatbotsAgent workflowsPrompt engineeringTool useAI-assisted application developmentStrong understanding of architecture principles, including:ModularityReusabilityScalabilityReliabilitySecurityMaintainabilityObservabilityCost awarenessExperience guiding teams through technical design, estimation, implementation, and production readiness.Strong troubleshooting and root-cause analysis skills across application code, integrations, logs, traces, telemetry, and production behavior.Experience mentoring, coaching, and influencing engineers without requiring direct reporting authority.Excellent communication skills with the ability to explain technical tradeoffs to engineers, product partners, business stakeholders, and senior leaders.Comfort operating in ambiguous, fast-moving environments where AI capabilities, tools, and platform patterns continue to evolve.Preferred QualificationsExperience with one or more of the following is helpful, but not required:Enterprise AI platform architectureAzure AI Foundry, Azure AI services, or similar cloud AI platformsAzure DevOps, Azure App Service, Azure API Management, or related Microsoft cloud toolsLLM application architecture using models from OpenAI, Anthropic, Microsoft, or similar providersAgentic applications and multi-agent workflow patternsRAG architecture, retrieval quality, chunking strategies, embeddings, vector databases, and rerankingModel Context Protocol, function calling, tool calling, or enterprise tool integration patternsMCP registry, tool governance, tool security, or act-as-user integration patternsDurable workflow platforms such as TemporalEvent-driven systems, message queues, or orchestration patternsSalesforce integrations or enterprise system integrationsObservability platforms such as Langfuse, New Relic, OpenTelemetry, Azure Log Analytics, or similar toolsAI evaluation frameworks, golden tests, prompt/version management, or quality measurement practicesSecure software design for systems that handle sensitive or regulated dataDevOps, infrastructure, deployment automation, containerization, or cloud-native application patternsAI-powered development tools such as Cursor, Claude Code, or similar toolsCreating technical demos, POCs, or internal enablement materials to help engineering teams adopt new technologiesTechnical documentation, architecture decision records, solution diagrams, and executive-level technical communicationWorking with SDETs, DevOps engineers, support engineers, software managers, product owners, and enterprise architectsKey Areas of OwnershipArchitecture DirectionSet technical direction for AI platform capabilities and implementation patterns.Partner with other architects to align team-level designs with broader platform strategy.Ensure solutions are secure, scalable, reliable, observable, and maintainable.Help teams make good tradeoff decisions around speed, quality, complexity, cost, and long-term supportability.AI Platform PatternsGuide architecture for LLM-powered agents, RAG pipelines, prompts, skills, tools, and workflows.Define reusable patterns for AI application development.Establish standards for tool integrations, orchestration, observability, evaluation, and production readiness.Support responsible AI engineering practices that improve accuracy, transparency, reliability, and user trust.Hands-On Technical LeadershipStay close to the codebase through regular code reviews, design reviews, POCs, reference implementations, and complex troubleshooting.Contribute directly to application, platform, workflow, integration, or agent code when senior technical involvement is needed.Build working demos, technical spikes, starter templates, and reference implementations.Experiment with emerging AI technologies, tools, models, frameworks, and orchestration patterns.Turn technical exploration into practical team guidance and reusable implementation standards.Assist with production issues requiring senior engineering judgment.Use hands-on learning and code-level involvement to coach engineers and raise the technical bar.Collaboration and CommunicationWork closely with program architects, application architects, software managers, engineers, SDETs, DevOps engineers, support teams, product partners, and business stakeholders.Explain architecture decisions and tradeoffs clearly.Document solution designs, patterns, diagrams, standards, and decision records.Promote reuse and consistency across teams.Help socialize new technologies, patterns, and platform capabilities.What Success Looks LikeYou will be successful in this role if you:Set clear technical direction that teams can actually execute.Help teams move faster without creating unnecessary complexity or long-term risk.Build reusable patterns that improve consistency, quality, and delivery speed.Make AI platform capabilities easier for teams to understand, use, test, and support.Remain close enough to the codebase to make architecture decisions that are practical, credible, and executable.Contribute directly when the team needs senior technical help.Turn emerging AI technologies into practical examples, demos, and reusable patterns.Mentor engineers and raise the technical bar across teams.Communicate architecture in a way that is useful to engineers, leaders, and business partners.Help the Enterprise AI Program scale from individual solutions to a repeatable platform model.SupervisionThis position does not have direct reports.However, this role provides technical leadership, mentoring, coaching, and architectural oversight across multiple scrum teams within the Enterprise AI Program.Be aware of employment fraud. All email communications from Ascensus or its hiring managers originate from @ascensus.com or @futureplan.com email addresses. We will never ask you for payment or require you to purchase any equipment. If you are suspicious or unsure about validity of a job posting, we strongly encourage you to apply directly through our website.SummaryLocation: Dresher, PA; Lake Mary, FLType: Full time