Principal Architect, HCLS

Presidio

About The Position

At Presidio, we’re at the forefront of a global technology revolution, transforming industries through cutting-edge digital solutions and next-generation AI. We empower businesses—and their customers—to achieve more through innovation, automation, and intelligent insights. A Presidio Digital Services Principal Architect, Healthcare and Life Sciences (HCLS), leads presales discovery, analysis, architecture, design, proposals, and scope-of-work creation, translating customer requirements into outcome-focused solutions through direct client engagement with HCLS accounts. Leveraging sharp business acumen alongside technical expertise, a builder mentality, presales methodology, and strong relationships (clients, Presidio stakeholders, and vendor partners); the Principal Architect assesses industry, customer, technical, and sales context to position solutions that deliver measurable, long-term value. This is a client-facing, 100% presales role that operates at the intersection of sales, delivery engineering, and customer executives to ensure we only propose solutions that are desirable for the client, feasible for delivery, and viable for Presidio

Requirements

Bachelor’s degree or equivalent experience and/or military experience
Overall 10+ years of relevant experience
7+ years of architecture, design, implementation, and/or consulting in digital and/or cloud technologies
5+ years hands-on experience with AWS, Azure, or GCP, with deep expertise in at least one major cloud and readiness to work with others
5+ years of specific domain experience in one or more of the following areas: Application development: Building new products, features, or user experiences
Application modernization: Refactoring legacy codebases, re-architecting monoliths, upgrading frameworks (beyond lift-and-shift or containerization only)
Data engineering and modernization: Modern data platforms (Snowflake, Databricks), data pipelines, large-scale data migration programs, analytics solutions, cloud-native data services (AWS Glue/Redshift/EMR, Azure Synapse/Data Factory, GCP BigQuery/Dataflow)
Software development lifecycle (SDLC) optimization: CI/CD for developer velocity, AI-augmented development, and testing automation
Artificial intelligence (AI) and Generative AI (GenAI): RAG pipelines, LLM-embedded applications, multi-agent systems, and agentic orchestration approaches
Extreme ownership mentality with a self-starting approach to ambiguous problems without waiting for direction
Demonstrated grit and resilience with a track record of running toward tough challenges and navigating uncertainty
Intellectual curiosity with evidence of independently learning emerging technologies (for example, GenAI, agentic AI, modern data platforms, or cloud services) outside formal training
Collaborative mindset with humility and the ability to work across sales, delivery engineering, and partner teams, deferring to domain experts when appropriate
Growth mindset with willingness to course-correct upon feedback and actively seek mentoring and coaching
Aptitude for consultative presales with a context-first problem-solving approach
Proven ability to deeply understand customer business friction, desired outcomes, and constraints before architecting solutions
Demonstrated comfort leading presentations, solution demonstrations, and whiteboard sessions with both technical and executive audiences
Expert time management and ability to set expectations and provide timely feedback loops to leadership and account teams
Hands-on engineering background with proven experience writing, reviewing, or refactoring code, or architecting data solutions (not just infrastructure or platform design)
Deep roots in software development or data engineering, with experience building, testing, and shipping software or data solutions
Prior experience in a presales solution architect, principal architect, or similar role bridging sales and delivery is strongly preferred
A builder mentality capable of prototyping software and data solution concepts where appropriate, with comfort using AI-accelerated tools as part of your own workflow

Nice To Haves

Amazon Web Services (AWS), Google (GCP), and/or Microsoft (Azure) architect-level certifications
Experience in delivering modern application architectures through hands-on development or code refactoring (for example, microservices, event-driven architectures, serverless, API-first design)
Hands-on software engineering or code development experience (for example, Python, Java, C#, JavaScript/TypeScript, Go, or similar)
Experience with modern data platforms and tools: Snowflake, Databricks, AWS (Glue, Redshift, EMR, Lake Formation), Azure (Synapse, Data Factory, Databricks), GCP (BigQuery, Dataflow, Dataproc)
Data engineering experience including building data pipelines, ETL/ELT, data modeling, data governance, or analytics solutions
Experience with large-scale data migration or modernization programs
Experience building GenAI-embedded solutions: RAG pipelines, LLM-based applications, prompt design, vector databases
Experience with agentic AI frameworks and orchestration: LangGraph, AutoGen, crewAI, Semantic Kernel, or custom multi-agent systems
Familiarity with data engineering for AI/ML, including feature engineering, vector databases, and data preparation for LLM training or fine-tuning
Familiarity with AI-accelerated development tools such as GitHub Copilot, Cursor, Amazon CodeWhisperer, Tabnine, or similar
Experience using AI in the SDLC, including code generation, automated testing, documentation generation, or code review assistance
Demonstrated curiosity about AI’s impact on software and data delivery (for example, through webinars, articles, experiments, or peer discussions)
DevOps experience focused on application delivery and developer productivity (rather than platform operations alone)
Experience with reviewing and/or writing statements of work (SOW)
Experience and/or ability to prepare RFP/RFI responses, proposals, and solution documents
Demonstrated comfort leading CIO/CTO-level presentations, solution demonstrations, and whiteboard sessions
Experience working in Healthcare and Life Sciences (HCLS) solutions, companies, or regulated environments
Awareness of GxP compliance frameworks, 21 CFR Part 11, HIPAA/PHI data handling, and related regulatory constraints
Familiarity with FHIR interoperability standards, HL7, and EHR/EMR integrations (for example, Epic, Cerner)
Understanding of clinical workflows, payer/provider dynamics, or life sciences R&D and commercialization processes