Solutions Architect

3Core Systems, Inc

. Own end-to-end architecture solutions for complex systems, balancing scalability, performance, security, and rapid delivery .

Posted 9/28/2026contractRemote • Illinois • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AI Architecture, including the design and implementation of scalable AI solutions and enterprise-scale distributed systems. Proficient in guiding teams through architectural decisions while ensuring compliance with security and regulatory standards.

Highest-signal resume keywords

AI Architecture ExperienceStrong Programming Background in Python and JavaCloud-Native Architectures with AWS, Docker, and KubernetesAPI Design Experience with REST, GraphQL, and gRPCExperience with RAG and Generative AI

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI Solution DesignEnterprise-Scale Distributed SystemsSQL and NoSQL DatabasesCI/CD and Infrastructure as CodeData Modeling and ReplicationArchitecting End-to-End AI WorkflowsEmbedding Techniques and Similarity SearchArchitectural Standards and Best PracticesProof of Concept DevelopmentArchitecting AI-Related Projects

Soft Skills

Ability to Influence Without AuthorityArticulation of Complex Technical ConceptsCollaboration with Business LeadersMentorship to Engineering TeamsProblem-Solving in Complex Architectures

Tools & Technologies

AWS ServicesDockerKubernetesVector DatabasesEvent-Driven ArchitecturesObservability ToolsAutomated Testing FrameworksArchitectural Documentation ToolsAI Reference ArchitecturesEmerging AI Technologies

Industry Keywords

Telematics IndustryAutomotive IndustryRegulatory ComplianceScalability StandardsPerformance Standards

Tech Stack

Tools & technologies

AssemblyAWSCloudDistributed SystemsDockerGraphQLGRPCJavaKubernetesNoSQLPythonSQL

About the role

Key responsibilities & impact

Own end-to-end architecture solutions for complex systems, balancing scalability, performance, security, and rapid delivery
Influence enterprise technology strategy
Define solution and platform architectures for large-scale distributed systems from concept through production
Create architectures meeting standards for scalability, performance, resilience, and security
Partner with business leaders, product owners, engineering managers, and delivery teams to align architecture with business outcomes
Assess, select, and introduce technologies through 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 architecture documentation, including rationale and tradeoffs
Evolve platform architecture to improve developer productivity, system reliability, and cost efficiency
Architect AI-related projects and communicate daily with US-based business owners and architecture team members

Requirements

What you’ll need

Candidates residing in the US; preferred location is Chicago or Peoria, IL area
Candidates should ideally be local; non-local candidates should be open to relocation/travel as required
Strong preference for experience in the telematics or automotive industry
At least 5–6 years of AI Architecture experience
Hands-on experience designing and owning AI solutions at an architect level
Strong experience with RAG and Generative AI
Bachelor's degree with 5+ years' experience in this capacity
Ability to decompose complex problem spaces and develop pragmatic architecture options with clearly articulated tradeoffs
Ability to influence without authority and guide teams through architectural decisions and implementation challenges
Ability to articulate complex technical concepts to technical and non-technical stakeholders
Ability to translate business and non-functional requirements into scalable technical designs
Strong foundation in modern application and platform architectures using established patterns and standards
Experience defining AI reference architectures and standards for enterprise adoption
Ability to explain and defend tradeoffs between classical ML, LLM-based approaches, and non-AI solutions
Proven experience taking AI systems from proof of concept to scaled production use
Strong programming background in Python and Java
Experience designing and building enterprise-scale distributed systems
Hands-on experience with cloud-native architectures, AWS services, Docker, and Kubernetes
Deep understanding of SQL and NoSQL databases, Snowflake, data modeling, replication, and sharding
Experience with CI/CD, infrastructure as code, observability, and automated testing
Strong API design experience with REST, GraphQL, and gRPC, including versioning and documentation
Ability to evaluate and introduce emerging technologies aligned to business goals
Hands-on experience designing RAG architectures, including data ingestion, document preprocessing, chunking, vectorization, embeddings, retrieval, ranking, and context assembly
Understanding of embedding techniques, similarity search, vector dimensions, chunk size and overlap, and latency/recall/cost tradeoffs
Experience with vector databases and search layers
Experience with agentic frameworks
Ability to architect end-to-end AI workflows, including prompt design/versioning, context management, memory patterns, model routing, and fallback strategies
Knowledge of LLM lifecycle considerations, including model selection, fine-tuning vs. RAG vs. hybrid approaches, evaluation, monitoring, and drift detection
Understanding of AI system non-functional requirements, including performance, latency, cost controls, token efficiency, security, data privacy, and guardrails
Experience integrating AI capabilities into enterprise platforms through APIs and event-driven architectures
Ability to assess, prototype, and productionize emerging AI technologies

Benefits

Comp & perks

100% remote work for candidates residing in the US
12-month contract