Solutions Architect-Principal Cloud & AI Platform Architect

Brickstech; United States; On-site; USD 180,000 - 240,000; Full time

Job summary

Brickstech seeks a Principal Digital Architect for AI projects, collaborating daily with US business owners and architecture teams. You will own end-to-end architectures for large-scale, distributed systems, balancing scalability, performance, security and rapid delivery while shaping enterprise technology strategy.

Top candidates design AI reference architectures, RAG pipelines, vector search, and agentic workflows, evaluating ML vs LLM vs non-AI approaches, with strong API design and

Qualifications

• Bachelor’s degree with 5+ years of AI/architecture experience.
• Strong background in scalable, enterprise-grade AI systems.
• Expertise with AWS, containerization, and modern DevOps practices.
• Proven ability to design and guide complex solution architectures.

Responsibilities

• Own end-to-end solution and platform architectures for large-scale distributed systems.
• Define AI reference architectures, RAG pipelines, vector search, and agentic workflows.
• Shape enterprise technology strategy and ensure security and compliance.
• Mentor engineering teams and translate ambiguous business needs into durable solutions.
• Produce architecture documentation and guide platform evolution for productivity.

Skills

AI

AWS

Enterprise Application

Java

LLM

Python

RAG

Solution Architecture

Education

Bachelor's degree

Tools

Docker

Kubernetes

Snowflake

SQL

NoSQL

REST/GraphQL/gRPC

Job description

Job Description

Visa:- (Any - Strictly No H1b)
This is a Principal Digital Architect role focused on AI-related projects, requiring daily collaboration with US-based business owners and architecture teams.
You will own end-to-end solution and platform architecture for large-scale, distributed systems, from concept to production.
The role demands balancing scalability, performance, security, resilience, and rapid delivery while shaping enterprise technology strategy.
Key work includes defining AI reference architectures, designing RAG pipelines, vector search, and agentic workflows, and taking AI from PoC to production.
You must be able to evaluate trade-offs between classical ML, LLM-based, and non-AI solutions, plus handle prompt design, model routing, evaluation, and cost/latency controls.
Required technical depth includes Python/Java, AWS, Docker/Kubernetes, SQL/NoSQL/Snowflake, modern DevOps, and strong API design (REST/GraphQL/gRPC).
You will also establish architectural standards, mentor engineering teams, and translate ambiguous business needs into durable solutions.
Top candidates have 5+ years experience, strong communication skills, and proven success building enterprise-scale AI systems with security and compliance.
Must have Skills-
AI, AWS, Enterprise Application, Java, LLM (Large Language Model), Python, RAG (Retrieval-Augmented Generation), Solution Architecture
RequiredEducation/Experience:
• Bachelor’sdegreewith5+yearsofexperienceinthiscapacity
RequiredQualifications:
• ThisisArchitecturepositionforAIrelatedprojectswhichrequiredailycommunicationswithbusinessownersandothermembersofarchitectureteamlocatedinUS
Position’sContributionstoWorkGroup:
• AsaPrincipalDigitalArchitect,youwillowntheendtoendarchitecturesolutionsforcomplexsystems—balancingscalability,performance,security,andrapiddelivery—whileinfluencingEnterprisetechnologystrategy.
• Thisrolerequiresstrongtechnicaldepth,architecturaljudgment,andtheabilitytotranslateambiguousbusinessneedsintodurable,scalablesolutions.
Typicaltaskbreakdown:
• Ownanddefinesolutionandplatformarchitecturesforlargescale,distributedsystemsfromconceptthroughproduction.
• Createarchitecturethatmeetshighstandardsforscalability,performance,resilience,andsecurity.
• Partnercloselywithbusinessleaders,productowners,engineeringmanagers,anddeliveryteamstoensurearchitecturalalignmentwithbusinessoutcomes.
• Assess,select,andintroducenewtechnologies,includingproofofconceptdevelopmentandarchitecturalspikes.
• Establishandenforcearchitecturalstandards,patterns,andbestpracticesacrossplatformteams.
• Providearchitecturalguidanceandmentorshiptoengineeringteams,ensuringhighqualityimplementation.
• Ensuresolutionsmeetsecurity,compliance,andregulatoryrequirements.
• Produceandmaintaincleararchitecturedocumentation,includingrationaleandtradeoffs.
• Continuouslyevolveplatformarchitecturetoimprovedeveloperproductivity,systemreliability,andcostefficiency.
RequiredTechnicalSkills:
• ArchitecturalThinking:Abilitytodecomposecomplexproblemspacesanddeveloppragmaticarchitectureoptionswithclearlyarticulatedtradeoffs.
• TechnicalLeadership:Influencewithoutauthority;guideteamsthrougharchitecturaldecisionsandimplementationchallenges.
• Communication:Clearlyarticulatecomplextechnicalconceptstobothtechnicalandnontechnicalstakeholders.
• RequirementsAnalysis:Translatebusinessandnonfunctionalrequirementsintoscalabletechnicaldesigns.
• Platform&ApplicationArchitecture:Strongfoundationindesigningmodernapplicationandplatformarchitecturesusingestablishedpatternsandstandards.
Considerationfortopcandidates:
• ExperiencedefiningAIreferencearchitecturesandstandardsforenterpriseadoption.
• AbilitytoexplainanddefendarchitecturaltradeoffsbetweenclassicalML,LLMbasedapproaches,andnonAIsolutions.
• ProvenexperiencetakingAIsystemsfromproofofconcepttoscaledproductionuse.
• StrongprogrammingbackgroundinPythonandJava,withtheabilitytoreasonatcodelevel.
• Provenexperiencedesigningandbuildingenterprisescale,distributedsystems.
• Handsonexperiencewithcloudnativearchitectures,includingAWSservices,containerization,andorchestration(Docker,Kubernetes).
• Deepunderstandingofdataarchitecture:SQLandNoSQLdatabases,datawarehouses(Snowflakespecifically),datamodeling,replication,andsharding.
• ExperiencewithmodernDevOpspractices:CI/CD,infrastructureascode,observability,andautomatedtesting.
• StrongAPIdesignexperience(REST,GraphQL,gRPC),includingversioninganddocumentation.
• Abilitytoevaluateandintroduceemergingtechnologiesalignedtobusinessgoals.
AIRelatedSkills:
• HandsonexperiencedesigningRetrievalAugmentedGeneration(RAG)architectures,including:
• Dataingestionpipelines
• Documentpreprocessingandchunkingstrategies
• Vectorizationandembeddingmodels
• Querytimeretrieval,ranking,andcontextassembly
• Deepunderstandingofembeddingtechniques,similaritysearch,andtradeoffsacross:
• Vectordimensions
• Chunksizeandoverlap
• Latencyvs.recallvs.cost
• Experiencewithvectordatabasesandsearchlayers(e.g.,managedorselfhostedvectorstores)andtheirintegrationintoapplicationarchitectures.
• ExperiencewithAgenticFrameworks
• AbilitytoarchitectendtoendAIworkflows,including:
• Promptdesignandpromptversioning
• Contextmanagementandmemorypatterns
• Modelroutingandfallbackstrategies
• KnowledgeofLLMlifecycleconsiderations,including:
• Modelselection(hostedvs.selfhosted)
• Finetuningvs.RAGvs.hybridapproaches
• Evaluation,monitoring,anddriftdetection
• StrongunderstandingofAIsystemnonfunctionalrequirements,including:
• Performanceandlatencyoptimization
• Costcontrolsandtokenefficiency
• Security,dataprivacy,andguardrails
• ExperienceintegratingAIcapabilitiesintoexistingenterpriseplatformsviaAPIsandeventdrivenarchitectures.
• Abilitytoassess,prototype,andproductionizeemergingAItechnologiesalignedtobusinessusecases.