Symphony Industrial AI, Inc.
Introduction
SymphonyAI is a leading enterprise AI software company that specializes in delivering AI-powered SaaS solutions across multiple verticals, with a particular focus on financial crime prevention and regulatory compliance. Our Financial Services division develops cutting-edge AI applications that help global financial institutions detect threats earlier, act decisively, and maintain superior compliance at scale. As Microsoft's 2024 Partner of the Year for AI Innovation within Business Transformation, SymphonyAI combines predictive and generative AI technologies to deliver measurable results for the world's leading financial institutions. Job Description
Position Summary
We are seeking an exceptional, hands‑on Chief Architect to serve as the technical visionary and architectural authority for SymphonyAI's Financial Services business unit. Reporting to the SVP, Engineering, this role will define and govern the end‑to‑end architecture across all SymphonyAI financial services applications, AI systems, data platform, and cloud infrastructure. The Chief Architect will be responsible for establishing architectural standards, ensuring technical excellence, and driving the evolution of our AI‑first platform architecture to deliver market‑leading financial risk and compliance management solutions. This is a strategic leadership position that requires deep technical expertise, systems thinking, and the ability to translate complex business requirements into scalable, secure, and compliant architectural solutions. The successful candidate will bridge cutting‑edge AI technology with enterprise financial services requirements while ensuring architectural coherence across our entire product portfolio. Experience designing enterprise scale, high volume transaction systems for Tier 1 Banking, Fintech, Payment Providers is a plus. Preferred Location
East Coast Based (NY, CT, NJ) Key Responsibilities
Strategic Architecture Leadership
Enterprise Architecture Vision:
Define and maintain the overall architectural vision, strategy, and roadmap for all SymphonyAI financial services applications, ensuring alignment with business objectives and technology strategy. AI‑First Architecture:
Lead the design and evolution of AI‑first system architectures that integrate predictive AI, generative AI, and agentic AI capabilities into financial crime prevention and compliance applications. Platform Architecture Strategy:
Drive the architectural evolution from legacy systems to modern cloud‑native, multi‑tenant SaaS platform architecture, ensuring scalability, performance, security, and regulatory compliance. Technology Standards & Governance:
Establish and enforce architectural standards, design patterns, technology selection criteria, and architectural governance processes across all product development initiatives. Innovation & Emerging Technology:
Evaluate emerging technologies (including LLMs, agentic AI frameworks, vector databases, and advanced AI/ML platforms) and define strategies for incorporating them into the product architecture. Architecture Design & Execution
Solution Architecture:
Lead the design and review of complex system architectures for high‑volume, high‑velocity financial transaction processing, real‑time risk decisioning, and compliance automation. Multi‑Agent Systems Architecture:
Design production‑ready, multi‑agent AI systems that enable orchestrated workflows, autonomous decisioning, and human‑in‑the‑loop capabilities for financial risk and compliance applications. Data Architecture:
Define comprehensive data architecture strategies including data modeling, ontology frameworks, data pipelines, data lakes, data warehouses, and real‑time data streaming architectures. Integration Architecture:
Design API‑first integration strategies, microservices architectures, and event‑driven patterns to support seamless connectivity with financial institution ecosystems and third‑party services. Cloud Infrastructure Architecture:
Lead cloud‑native architecture design for hybrid and multi‑cloud environments (AWS, Azure, GCP), ensuring optimal performance, cost‑effectiveness, security, and disaster recovery capabilities. Security Architecture:
Collaborate with InfoSec and Compliance teams to ensure all architectural solutions meet stringent regulatory requirements, data privacy standards (GDPR, CCPA, SOC2), and zero‑trust security principles. Technical Governance & Quality Assurance
Architecture Review Boards:
Establish and lead Architecture Review Board (ARB) processes to evaluate project architectures, ensure compliance with standards, and approve architectural decisions and exceptions. Technical Debt Management:
Develop and implement frameworks to assess, score, prioritize, and remediate architectural and technical debt across the enterprise application portfolio. Architecture Assurance:
Ensure technical integrity of all designs, identify reusable architectural components, eliminate unnecessary duplication, and maintain architectural consistency across products. Performance & Scalability:
Define performance benchmarks, scalability requirements, and optimization strategies to ensure systems meet enterprise‑scale deployment requirements. Quality Standards:
Establish architecture quality metrics, conduct architectural reviews at key milestones, and ensure adherence to engineering best practices. Cross‑Functional Collaboration & Leadership
Partnership:
Serve as the SVP's trusted technical advisor and right‑hand partner on all architectural matters, translating strategic technology vision into executable architectur‑al blueprints. Engineering Team Collaboration:
Partner closely with engineering leaders, development teams, data science teams, and DevOps teams to ensure architectural principles are understood and implemented correctly. Product Management Alignment:
Collaborate with Product Management to translate business requirements and feature roadmaps into technical architecture specifications and ensure feasibility of product initiatives. Stakeholder Communication:
Communicate complex architectural concepts to both technical and non‑technical audiences, including executive leadership, engineering teams, and external partners. Architecture Team Leadership:
Build and mentor a team of solution architects, data architects, security architects, and infrastructure architects, fostering a culture of technical excellence and continuous learning. AI & Machine Learning Architecture
ML Platform Architecture:
Design and oversee scalable machine learning infrastructure that supports model training, deployment, monitoring, and continuous improvement for real‑time transaction monitoring and risk assessment. MLOps Framework:
Define MLOps practices, CI/CD pipelines for models, model versioning, model governance, and model observability frameworks. Responsible AI Architecture:
Ensure AI architectures incorporate explainability, transparency, fairness, bias detection, and model risk management capabilities to meet regulatory confidence requirements. Ontology & Knowledge Graphs:
Lead the design of industry‑leading ontology frameworks and knowledge graph architectures for financial services data operations. AI User Experience Architecture:
Define architectural patterns for delivering AI‑first user experiences across different user personas (investigators, analysts, compliance officers, executives). Platform Modernization & Transformation
Legacy System Migration:
Architect phased migration strategies to transition from legacy systems to modern platform architecture while maintaining operational continuity and minimal customer disruption. Microservices Transformation:
Lead the decomposition of monolithic applications into microservices architectures with clear service boundaries, API contracts, and dependency management. Containerization & Orchestration:
Define container strategies using Docker and Kubernetes, including service mesh architectures, container security, and orchestration patterns. DevOps & CI/CD Architecture:
Establish continuous integration and continuous deployment pipeline architectures, infrastructure‑as‑code practices, and automated testing frameworks. Required Qualifications
Education & Experience
Bachelor's degree in Computer Science, Engineering, or related technical field; Master's degree strongly preferred. 12+ years of progressive technology experience with deep expertise in enterprise software architecture. 7+ years in senior architecture roles (Chief Architect, Principal Architect, Enterprise Architect, or equivalent). 5+ years of experience in FinTech, financial services, or payments technology with exposure to financial crime prevention, compliance, or risk management systems. Hands‑on experience designing enterprise scale, high volume transaction systems for Tier 1 Banking, FinTech, Payment Providers. Technical Expertise
Enterprise Architecture Mastery:
Deep expertise in enterprise architecture frameworks (TOGAF, Zachman), architecture governance models, and large‑scale system design patterns. SaaS Architecture:
Proven experience designing and scaling multi‑tenant SaaS platforms, with specific experience in financial services applications and regulatory compliance requirements. AI/ML Architecture:
Extensive knowledge of AI/ML architectures, including deep learning frameworks (PyTorch, TensorFlow), LLM architectures, RAG (Retrieval‑Augmented Generation) patterns, agentic AI systems, and ML platform engineering. Cloud Architecture Expertise:
Expert‑level experience with major cloud platforms (AWS, Azure, GCP), cloud‑native architecture patterns, serverless computing, and cloud cost optimization. Data Architecture:
Strong expertise in data modeling, data warehousing (Snowflake, Redshift, BigQuery), data lakes, real‑time streaming (Kafka, Kinesis), and modern data stack architectures. Microservices & APIs:
Deep understanding of microservices architectures, RESTful and GraphQL API design, event‑driven architectures, and service mesh technologies (Istio, Linkerd). DevOps & Infrastructure:
Strong knowledge of CI/CD pipelines, infrastructure‑as‑code (Terraform, CloudFormation), containerization (Docker, Kubernetes), and GitOps practices. Architecture Leadership Skills
Systems Thinking:
Exceptional ability to understand complex interdependencies across business units, platforms, and technologies, and design coherent end‑to‑end solutions. Strategic Vision:
Demonstrated ability to translate business strategy into multi‑year technical architecture roadmaps that balance innovation with pragmatism. Technical Communication:
Outstanding ability to communicate complex technical concepts to diverse audiences, from developers to C‑suite executives and board members. Decision Making:
Strong analytical and decision‑making skills with ability to evaluate trade‑offs and make architectural decisions based on multiple variables and constraints. Influence & Collaboration:
Proven ability to influence without direct authority, build consensus across distributed teams, and drive architectural standards adoption. Regulatory & Domain Knowledge
Financial Services Expertise:
Deep understanding of financial services technology stack including payment processing, transaction monitoring, regulatory reporting, and compliance systems to Tier 1 Banks, FinTechs, etc. Regulatory Architecture:
Experience designing systems that meet regulatory requirements including AML, KYC, sanctions screening, fraud detection, and audit trail requirements. Data Privacy & Security:
Expertise in data governance, privacy regulations (GDPR, CCPA, SOC2), security architecture patterns, and secure data handling in financial services. Preferred Qualifications
Advanced Technical Skills
Hands‑on experience with agentic AI architectures, autonomous agent frameworks (LangChain, AutoGen, CrewAI), and multi‑agent orchestration patterns. Experience with vector databases (Pinecone, Weaviate, ChromaDB) and embedding architectures for semantic search and RAG applications. Advanced certifications in cloud platforms (AWS Solutions Architect Professional, Azure Solutions Architect Expert, GCP Professional Cloud Architect). Experience with graph databases (Neo4j, TigerGraph) and knowledge graph architectures for financial services ontologies. Industry Experience
Prior experience architecting core banking systems, payment platforms, credit decisioning engines, or fraud detection systems. Background in RegTech or compliance technology architecture with understanding of regulatory technology requirements. Experience with blockchain and cryptocurrency architectures, particularly for transaction monitoring and compliance applications. Familiarity with real‑time decisioning architectures and complex event processing (CEP) systems. Leadership Experience
Experience building and leading distributed architecture teams across onshore and offshore locations. Track record of architecting systems that successfully scaled from startup through enterprise scale. Published thought leadership in architecture, AI, financial technology, or compliance domains through conferences, blogs, or technical papers. Active participation in industry standards bodies, open‑source communities, or technology advisory boards. About Us
SymphonyAI is building the leading enterprise AI SaaS company for digital transformation across the most critical and resilient growth industries, including retail, consumer packaged goods, financial crime prevention, manufacturing, media, and IT service management. Since its founding in 2017, SymphonyAI today serves 1500+ Enterprise customers globally and has grown to 3,000 talented leaders, data scientists, and other professionals across over 30 countries. #LI‑Remote
#J-18808-Ljbffr
SymphonyAI is a leading enterprise AI software company that specializes in delivering AI-powered SaaS solutions across multiple verticals, with a particular focus on financial crime prevention and regulatory compliance. Our Financial Services division develops cutting-edge AI applications that help global financial institutions detect threats earlier, act decisively, and maintain superior compliance at scale. As Microsoft's 2024 Partner of the Year for AI Innovation within Business Transformation, SymphonyAI combines predictive and generative AI technologies to deliver measurable results for the world's leading financial institutions. Job Description
Position Summary
We are seeking an exceptional, hands‑on Chief Architect to serve as the technical visionary and architectural authority for SymphonyAI's Financial Services business unit. Reporting to the SVP, Engineering, this role will define and govern the end‑to‑end architecture across all SymphonyAI financial services applications, AI systems, data platform, and cloud infrastructure. The Chief Architect will be responsible for establishing architectural standards, ensuring technical excellence, and driving the evolution of our AI‑first platform architecture to deliver market‑leading financial risk and compliance management solutions. This is a strategic leadership position that requires deep technical expertise, systems thinking, and the ability to translate complex business requirements into scalable, secure, and compliant architectural solutions. The successful candidate will bridge cutting‑edge AI technology with enterprise financial services requirements while ensuring architectural coherence across our entire product portfolio. Experience designing enterprise scale, high volume transaction systems for Tier 1 Banking, Fintech, Payment Providers is a plus. Preferred Location
East Coast Based (NY, CT, NJ) Key Responsibilities
Strategic Architecture Leadership
Enterprise Architecture Vision:
Define and maintain the overall architectural vision, strategy, and roadmap for all SymphonyAI financial services applications, ensuring alignment with business objectives and technology strategy. AI‑First Architecture:
Lead the design and evolution of AI‑first system architectures that integrate predictive AI, generative AI, and agentic AI capabilities into financial crime prevention and compliance applications. Platform Architecture Strategy:
Drive the architectural evolution from legacy systems to modern cloud‑native, multi‑tenant SaaS platform architecture, ensuring scalability, performance, security, and regulatory compliance. Technology Standards & Governance:
Establish and enforce architectural standards, design patterns, technology selection criteria, and architectural governance processes across all product development initiatives. Innovation & Emerging Technology:
Evaluate emerging technologies (including LLMs, agentic AI frameworks, vector databases, and advanced AI/ML platforms) and define strategies for incorporating them into the product architecture. Architecture Design & Execution
Solution Architecture:
Lead the design and review of complex system architectures for high‑volume, high‑velocity financial transaction processing, real‑time risk decisioning, and compliance automation. Multi‑Agent Systems Architecture:
Design production‑ready, multi‑agent AI systems that enable orchestrated workflows, autonomous decisioning, and human‑in‑the‑loop capabilities for financial risk and compliance applications. Data Architecture:
Define comprehensive data architecture strategies including data modeling, ontology frameworks, data pipelines, data lakes, data warehouses, and real‑time data streaming architectures. Integration Architecture:
Design API‑first integration strategies, microservices architectures, and event‑driven patterns to support seamless connectivity with financial institution ecosystems and third‑party services. Cloud Infrastructure Architecture:
Lead cloud‑native architecture design for hybrid and multi‑cloud environments (AWS, Azure, GCP), ensuring optimal performance, cost‑effectiveness, security, and disaster recovery capabilities. Security Architecture:
Collaborate with InfoSec and Compliance teams to ensure all architectural solutions meet stringent regulatory requirements, data privacy standards (GDPR, CCPA, SOC2), and zero‑trust security principles. Technical Governance & Quality Assurance
Architecture Review Boards:
Establish and lead Architecture Review Board (ARB) processes to evaluate project architectures, ensure compliance with standards, and approve architectural decisions and exceptions. Technical Debt Management:
Develop and implement frameworks to assess, score, prioritize, and remediate architectural and technical debt across the enterprise application portfolio. Architecture Assurance:
Ensure technical integrity of all designs, identify reusable architectural components, eliminate unnecessary duplication, and maintain architectural consistency across products. Performance & Scalability:
Define performance benchmarks, scalability requirements, and optimization strategies to ensure systems meet enterprise‑scale deployment requirements. Quality Standards:
Establish architecture quality metrics, conduct architectural reviews at key milestones, and ensure adherence to engineering best practices. Cross‑Functional Collaboration & Leadership
Partnership:
Serve as the SVP's trusted technical advisor and right‑hand partner on all architectural matters, translating strategic technology vision into executable architectur‑al blueprints. Engineering Team Collaboration:
Partner closely with engineering leaders, development teams, data science teams, and DevOps teams to ensure architectural principles are understood and implemented correctly. Product Management Alignment:
Collaborate with Product Management to translate business requirements and feature roadmaps into technical architecture specifications and ensure feasibility of product initiatives. Stakeholder Communication:
Communicate complex architectural concepts to both technical and non‑technical audiences, including executive leadership, engineering teams, and external partners. Architecture Team Leadership:
Build and mentor a team of solution architects, data architects, security architects, and infrastructure architects, fostering a culture of technical excellence and continuous learning. AI & Machine Learning Architecture
ML Platform Architecture:
Design and oversee scalable machine learning infrastructure that supports model training, deployment, monitoring, and continuous improvement for real‑time transaction monitoring and risk assessment. MLOps Framework:
Define MLOps practices, CI/CD pipelines for models, model versioning, model governance, and model observability frameworks. Responsible AI Architecture:
Ensure AI architectures incorporate explainability, transparency, fairness, bias detection, and model risk management capabilities to meet regulatory confidence requirements. Ontology & Knowledge Graphs:
Lead the design of industry‑leading ontology frameworks and knowledge graph architectures for financial services data operations. AI User Experience Architecture:
Define architectural patterns for delivering AI‑first user experiences across different user personas (investigators, analysts, compliance officers, executives). Platform Modernization & Transformation
Legacy System Migration:
Architect phased migration strategies to transition from legacy systems to modern platform architecture while maintaining operational continuity and minimal customer disruption. Microservices Transformation:
Lead the decomposition of monolithic applications into microservices architectures with clear service boundaries, API contracts, and dependency management. Containerization & Orchestration:
Define container strategies using Docker and Kubernetes, including service mesh architectures, container security, and orchestration patterns. DevOps & CI/CD Architecture:
Establish continuous integration and continuous deployment pipeline architectures, infrastructure‑as‑code practices, and automated testing frameworks. Required Qualifications
Education & Experience
Bachelor's degree in Computer Science, Engineering, or related technical field; Master's degree strongly preferred. 12+ years of progressive technology experience with deep expertise in enterprise software architecture. 7+ years in senior architecture roles (Chief Architect, Principal Architect, Enterprise Architect, or equivalent). 5+ years of experience in FinTech, financial services, or payments technology with exposure to financial crime prevention, compliance, or risk management systems. Hands‑on experience designing enterprise scale, high volume transaction systems for Tier 1 Banking, FinTech, Payment Providers. Technical Expertise
Enterprise Architecture Mastery:
Deep expertise in enterprise architecture frameworks (TOGAF, Zachman), architecture governance models, and large‑scale system design patterns. SaaS Architecture:
Proven experience designing and scaling multi‑tenant SaaS platforms, with specific experience in financial services applications and regulatory compliance requirements. AI/ML Architecture:
Extensive knowledge of AI/ML architectures, including deep learning frameworks (PyTorch, TensorFlow), LLM architectures, RAG (Retrieval‑Augmented Generation) patterns, agentic AI systems, and ML platform engineering. Cloud Architecture Expertise:
Expert‑level experience with major cloud platforms (AWS, Azure, GCP), cloud‑native architecture patterns, serverless computing, and cloud cost optimization. Data Architecture:
Strong expertise in data modeling, data warehousing (Snowflake, Redshift, BigQuery), data lakes, real‑time streaming (Kafka, Kinesis), and modern data stack architectures. Microservices & APIs:
Deep understanding of microservices architectures, RESTful and GraphQL API design, event‑driven architectures, and service mesh technologies (Istio, Linkerd). DevOps & Infrastructure:
Strong knowledge of CI/CD pipelines, infrastructure‑as‑code (Terraform, CloudFormation), containerization (Docker, Kubernetes), and GitOps practices. Architecture Leadership Skills
Systems Thinking:
Exceptional ability to understand complex interdependencies across business units, platforms, and technologies, and design coherent end‑to‑end solutions. Strategic Vision:
Demonstrated ability to translate business strategy into multi‑year technical architecture roadmaps that balance innovation with pragmatism. Technical Communication:
Outstanding ability to communicate complex technical concepts to diverse audiences, from developers to C‑suite executives and board members. Decision Making:
Strong analytical and decision‑making skills with ability to evaluate trade‑offs and make architectural decisions based on multiple variables and constraints. Influence & Collaboration:
Proven ability to influence without direct authority, build consensus across distributed teams, and drive architectural standards adoption. Regulatory & Domain Knowledge
Financial Services Expertise:
Deep understanding of financial services technology stack including payment processing, transaction monitoring, regulatory reporting, and compliance systems to Tier 1 Banks, FinTechs, etc. Regulatory Architecture:
Experience designing systems that meet regulatory requirements including AML, KYC, sanctions screening, fraud detection, and audit trail requirements. Data Privacy & Security:
Expertise in data governance, privacy regulations (GDPR, CCPA, SOC2), security architecture patterns, and secure data handling in financial services. Preferred Qualifications
Advanced Technical Skills
Hands‑on experience with agentic AI architectures, autonomous agent frameworks (LangChain, AutoGen, CrewAI), and multi‑agent orchestration patterns. Experience with vector databases (Pinecone, Weaviate, ChromaDB) and embedding architectures for semantic search and RAG applications. Advanced certifications in cloud platforms (AWS Solutions Architect Professional, Azure Solutions Architect Expert, GCP Professional Cloud Architect). Experience with graph databases (Neo4j, TigerGraph) and knowledge graph architectures for financial services ontologies. Industry Experience
Prior experience architecting core banking systems, payment platforms, credit decisioning engines, or fraud detection systems. Background in RegTech or compliance technology architecture with understanding of regulatory technology requirements. Experience with blockchain and cryptocurrency architectures, particularly for transaction monitoring and compliance applications. Familiarity with real‑time decisioning architectures and complex event processing (CEP) systems. Leadership Experience
Experience building and leading distributed architecture teams across onshore and offshore locations. Track record of architecting systems that successfully scaled from startup through enterprise scale. Published thought leadership in architecture, AI, financial technology, or compliance domains through conferences, blogs, or technical papers. Active participation in industry standards bodies, open‑source communities, or technology advisory boards. About Us
SymphonyAI is building the leading enterprise AI SaaS company for digital transformation across the most critical and resilient growth industries, including retail, consumer packaged goods, financial crime prevention, manufacturing, media, and IT service management. Since its founding in 2017, SymphonyAI today serves 1500+ Enterprise customers globally and has grown to 3,000 talented leaders, data scientists, and other professionals across over 30 countries. #LI‑Remote
#J-18808-Ljbffr