Infoverity
Data & AI Architect
Infoverity is seeking a Data & AI Architect to design, build and scale enterprise data and AI solutions. In this strategic role you will bridge the gap between business objectives and technical execution, architecting scalable AI solutions that deliver measurable business value.
You will work across modern data platforms (Databricks, Snowflake, Microsoft Fabric, etc.) and cloud ecosystems, supporting the full lifecycle from data ingestion and modeling through AI enablement, agent deployment and production operations. This is a hands‑on, consultative role requiring strong architectural judgment, customer engagement skills and the ability to guide solutions from proof‑of‑value to enterprise scale.
Key Responsibilities Architecture, Strategy & Roadmapping
Define Data & AI Strategy:
Partner with business and technical stakeholders to translate enterprise challenges into data, analytics and AI solution architectures, producing clear roadmaps, reference architectures and implementation plans.
Enterprise Integration:
Architect solutions integrating with enterprise source systems, APIs, operational platforms and downstream consuming layers.
Standards & Governance:
Establish design patterns and technical standards across data management, analytics and AI—covering security, scalability, performance, lineage and compliance requirements.
Data Platform & Ecosystem Design
Modern Data Stack Architecture:
Design and implement scalable data pipelines, transformation layers and orchestration frameworks across platforms such شورای Databricks, Snowflake, Microsoft Fabric, GCP or similar.
Analytics & Semantic Layers:
Support dimensional modeling, feature stores and semantic layers to enable BI, advanced analytics and AI workloads.
Cloud Infrastructure:
Design secure and best‑practice architectures on AWS, Azure or GCP, leveraging managed services, serverless patterns and containerised workloads (Docker/Kubernetes) where appropriate.
AI Enablement on Data Platforms:
Enable AI and ML mufflects using curated, governed enterprise data—supporting model training, inference and retrieval‑based architectures (e.g. RAG).
Agent‑Based Architectures:
Design and deploy agentic or workflow‑driven AI solutions, incorporating orchestration, tool/function calling, guardrails and observability to support multi‑step business processes.
television Prototyping to Production:
Lead Proof junction‑of‑Concept and pilot initiatives, validating business value and technical feasibility before scaling to production‑grade solutions.
Technical Leadership:
Review solution designs, contribute to critical implementation components and mentor engineers across data engineering, analytics and AI best practices.
Cross‑Team Collaboration:
Partner with delivery leads and stakeholders to manage technical risks, trade‑offs and dependencies across project lifecycles.
Operational Readiness亿元:
Support deployment, monitoring and optimisation of data and AI solutions to ensure reliability, performance and long‑term maintainability.
Delivery, Leadership & Enablement
Technical Leadership:
Review solution designs, contribute to implementation components and mentor engineers.
Cross‑Team Collaboration:
Partner with delivery leads and stakeholders to manage technical risks, trade‑offs and dependencies.
Operational Readiness:
Support deployment, monitoring and optimisation of data and AI solutions.
Qualifications Experience & Background
Professional Experience:
5+ years in data engineering, software engineering or solution architecture, with experience spanning data platforms and analytics or AI workloads.
Cloud Platforms:
Strong hands‑on experience with AWS or Azure, including data, analytics and AI‑related services.
Data Platforms:
Proven experience designing or implementing solutions on Databricks, Snowflake, Microsoft Fabric or similar platforms.
Technical Skills
Data Engineering:
Strong understanding of data ingestion, transformation, orchestration and modelling patterns.
AI & Agentic Architecture:
Familiarity with generative AI concepts (LLMs, embeddings, RAG), ML workflows and how AI integrates with enterprise data platforms.
MLOps / DataOps:
Experience with CI/CD, model or pipeline deployment, monitoring, lineage and governance tooling (e.g. MLflow, orchestration frameworks).
Architecture Patterns:
Experience with microservices, APIs, event‑driven architectures and containerisation.
Programming:
Proficiency in SQL, Python, Spark and distributed data‑processing frameworks.
Excellent problem‑solving, communication and client‑facing consulting skills.
Work Style:
Ability to work independently and as part of a team.
persoane>
Competencies & Soft Skills
Business Alignment:
Ability to connect data and AI capabilities to measurable business outcomes.
Communication:
Comfortable explaining architectural decisions to both technical and non‑technical audiences.
Enterprise Mindset:
Strong appreciation for security, governance, compliance and operational rigor in large organisations.
Preferred Qualifications
Degree in Computer Science, Data Engineering, Data Science or related field.
Cloud or platform certifications (AWS, Azure, Databricks, Snowflake).
Experience working in consulting or customer‑facing delivery environments. 嘉族
Benefits
Infoverity's benefits program is designed to provide comprehensive, affordable medical, dental, vision coverage and support for you and your family.Life and disability insurance, a wide‑ranging employee assistance programme (EAP) and pet insurance.
401(k) plan with competitive employer contributions.
Charity match program.
Professional development and upskilling opportunities.
Flexible hours and hybrid/remote work.
Company is 100% employee‑owned (ESOP).
Equal Employment Opportunity Infoverity is an equal opportunity employer. We celebrate diversity and are committed to fostering, cultivating and preserving a culture of inclusion. We believe that our people are our most valuable asset. The collective sum of the individual differences, life experiences, knowledge and Knit‑capabilities that our employees invest in their work represents our strength.
Seniority level Mid‑Senior level
Employment type Full‑time
Industries IT Services and IT Consulting
Referrals increase your Poli) chances of interviewing at Infoverity by 2x.
Sign in to set job alerts for “Architect” roles.
#J-18808-Ljbffr
You will work across modern data platforms (Databricks, Snowflake, Microsoft Fabric, etc.) and cloud ecosystems, supporting the full lifecycle from data ingestion and modeling through AI enablement, agent deployment and production operations. This is a hands‑on, consultative role requiring strong architectural judgment, customer engagement skills and the ability to guide solutions from proof‑of‑value to enterprise scale.
Key Responsibilities Architecture, Strategy & Roadmapping
Define Data & AI Strategy:
Partner with business and technical stakeholders to translate enterprise challenges into data, analytics and AI solution architectures, producing clear roadmaps, reference architectures and implementation plans.
Enterprise Integration:
Architect solutions integrating with enterprise source systems, APIs, operational platforms and downstream consuming layers.
Standards & Governance:
Establish design patterns and technical standards across data management, analytics and AI—covering security, scalability, performance, lineage and compliance requirements.
Data Platform & Ecosystem Design
Modern Data Stack Architecture:
Design and implement scalable data pipelines, transformation layers and orchestration frameworks across platforms such شورای Databricks, Snowflake, Microsoft Fabric, GCP or similar.
Analytics & Semantic Layers:
Support dimensional modeling, feature stores and semantic layers to enable BI, advanced analytics and AI workloads.
Cloud Infrastructure:
Design secure and best‑practice architectures on AWS, Azure or GCP, leveraging managed services, serverless patterns and containerised workloads (Docker/Kubernetes) where appropriate.
AI Enablement on Data Platforms:
Enable AI and ML mufflects using curated, governed enterprise data—supporting model training, inference and retrieval‑based architectures (e.g. RAG).
Agent‑Based Architectures:
Design and deploy agentic or workflow‑driven AI solutions, incorporating orchestration, tool/function calling, guardrails and observability to support multi‑step business processes.
television Prototyping to Production:
Lead Proof junction‑of‑Concept and pilot initiatives, validating business value and technical feasibility before scaling to production‑grade solutions.
Technical Leadership:
Review solution designs, contribute to critical implementation components and mentor engineers across data engineering, analytics and AI best practices.
Cross‑Team Collaboration:
Partner with delivery leads and stakeholders to manage technical risks, trade‑offs and dependencies across project lifecycles.
Operational Readiness亿元:
Support deployment, monitoring and optimisation of data and AI solutions to ensure reliability, performance and long‑term maintainability.
Delivery, Leadership & Enablement
Technical Leadership:
Review solution designs, contribute to implementation components and mentor engineers.
Cross‑Team Collaboration:
Partner with delivery leads and stakeholders to manage technical risks, trade‑offs and dependencies.
Operational Readiness:
Support deployment, monitoring and optimisation of data and AI solutions.
Qualifications Experience & Background
Professional Experience:
5+ years in data engineering, software engineering or solution architecture, with experience spanning data platforms and analytics or AI workloads.
Cloud Platforms:
Strong hands‑on experience with AWS or Azure, including data, analytics and AI‑related services.
Data Platforms:
Proven experience designing or implementing solutions on Databricks, Snowflake, Microsoft Fabric or similar platforms.
Technical Skills
Data Engineering:
Strong understanding of data ingestion, transformation, orchestration and modelling patterns.
AI & Agentic Architecture:
Familiarity with generative AI concepts (LLMs, embeddings, RAG), ML workflows and how AI integrates with enterprise data platforms.
MLOps / DataOps:
Experience with CI/CD, model or pipeline deployment, monitoring, lineage and governance tooling (e.g. MLflow, orchestration frameworks).
Architecture Patterns:
Experience with microservices, APIs, event‑driven architectures and containerisation.
Programming:
Proficiency in SQL, Python, Spark and distributed data‑processing frameworks.
Excellent problem‑solving, communication and client‑facing consulting skills.
Work Style:
Ability to work independently and as part of a team.
persoane>
Competencies & Soft Skills
Business Alignment:
Ability to connect data and AI capabilities to measurable business outcomes.
Communication:
Comfortable explaining architectural decisions to both technical and non‑technical audiences.
Enterprise Mindset:
Strong appreciation for security, governance, compliance and operational rigor in large organisations.
Preferred Qualifications
Degree in Computer Science, Data Engineering, Data Science or related field.
Cloud or platform certifications (AWS, Azure, Databricks, Snowflake).
Experience working in consulting or customer‑facing delivery environments. 嘉族
Benefits
Infoverity's benefits program is designed to provide comprehensive, affordable medical, dental, vision coverage and support for you and your family.Life and disability insurance, a wide‑ranging employee assistance programme (EAP) and pet insurance.
401(k) plan with competitive employer contributions.
Charity match program.
Professional development and upskilling opportunities.
Flexible hours and hybrid/remote work.
Company is 100% employee‑owned (ESOP).
Equal Employment Opportunity Infoverity is an equal opportunity employer. We celebrate diversity and are committed to fostering, cultivating and preserving a culture of inclusion. We believe that our people are our most valuable asset. The collective sum of the individual differences, life experiences, knowledge and Knit‑capabilities that our employees invest in their work represents our strength.
Seniority level Mid‑Senior level
Employment type Full‑time
Industries IT Services and IT Consulting
Referrals increase your Poli) chances of interviewing at Infoverity by 2x.
Sign in to set job alerts for “Architect” roles.
#J-18808-Ljbffr