Principal Digital Architect

Diversified Services Network, Inc.

19h•$125,000 - $130,000•Remote

About The Position

Diversified Services Network, Inc. (DSN) is seeking a full-time Principal Digital Architect to join our team! We offer full benefits, PTO, 401k, and more! This is a fully remote role for candidates residing in the US, with a preferred location near Chicago, IL or Peoria, IL. If you are a seasoned architect ready to own end-to-end solutions for complex systems and influence enterprise technology strategy within an extremely reputable, stable Fortune 500 company — let’s talk! Position Overview We are seeking a Principal Digital Architect to play a key role owning end-to-end architecture solutions for complex systems - balancing scalability, performance, security, and rapid delivery - while influencing enterprise technology strategy. This role requires strong technical depth, architectural judgment, and the ability to translate ambiguous business needs into durable, scalable solutions. You will join a team of 18.

Requirements

Bachelor’s degree required with 5+ years of relevant experience.
Architectural thinking — ability to decompose complex problem spaces and develop pragmatic architecture options with clearly articulated trade-offs.
Technical leadership — ability to influence without authority and guide teams through architectural decisions and implementation challenges.
Strong communication skills — ability to clearly articulate complex technical concepts to both technical and non-technical stakeholders.
Requirements analysis — ability to translate business and non-functional requirements into scalable technical designs.
Platform and application architecture — strong foundation in designing modern application and platform architectures using established patterns and standards.
Strong programming background in Python and Java, with the ability to reason at the code level.
Proven experience designing and building enterprise-scale, distributed systems; hands-on experience with cloud-native architectures, including AWS services, containerization, and orchestration (Docker, Kubernetes).
Deep understanding of data architecture, including SQL and NoSQL databases, data warehouses (Snowflake specifically), data modeling, replication, and sharding.
Experience with modern DevOps practices, including CI/CD, infrastructure as code, observability, and automated testing.
Strong API design experience (REST, GraphQL, gRPC), including versioning and documentation; ability to evaluate and introduce emerging technologies aligned to business goals.

Nice To Haves

Experience defining AI reference architectures and standards for enterprise adoption; ability to explain and defend architectural trade-offs between classical ML, LLM-based approaches, and non-AI solutions.
Proven experience taking AI systems from proof of concept to scaled production use, including hands-on Retrieval Augmented Generation (RAG) architecture design — data ingestion pipelines, document preprocessing/chunking strategies, vectorization and embedding models, and query-time retrieval, ranking, and context assembly.
Deep understanding of embedding techniques, similarity search, and related trade-offs (vector dimensions, chunk size/overlap, latency vs. recall vs. cost); experience with vector databases and search layers and their integration into application architectures.
Experience with agentic frameworks and the ability to architect end-to-end AI workflows, including prompt design and versioning, context management and memory patterns, and model routing/fallback strategies.
Knowledge of LLM lifecycle considerations — model selection (hosted vs. self-hosted), fine-tuning vs. RAG vs. hybrid approaches, and evaluation, monitoring, and drift detection.
Strong understanding of AI system non-functional requirements, including performance/latency optimization, cost controls and token efficiency, and security, data privacy, and guardrails.
Experience integrating AI capabilities into existing enterprise platforms via APIs and event-driven architectures; ability to assess, prototype, and productionize emerging AI technologies aligned to business use cases.

Responsibilities

Own and define solution and platform architectures for large-scale, distributed systems from concept through production, meeting high standards for scalability, performance, resilience, and security.
Partner closely with business leaders, product owners, engineering managers, and delivery teams to ensure architectural alignment with business outcomes.
Assess, select, and introduce new technologies, including proof of concept development and architectural spikes.
Establish and enforce architectural standards, patterns, and best practices across platform teams; provide architectural guidance and mentorship to engineering teams.
Ensure solutions meet security, compliance, and regulatory requirements; produce and maintain clear architecture documentation, including rationale and trade-offs.
Continuously evolve platform architecture to improve developer productivity, system reliability, and cost efficiency.