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Sr AI Architect ( Finance Technology AI Enablement) (Only W2))

Trispark Inc

Remote • Yesterday

Easy Apply

Contract

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Easy Apply

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Full-time

USD 145,200.00 - 217,800.00 per year

Trispark Inc

Job Details

Skills

Data Flow
Collaboration
Design Review
Finance
Database
Banking
API
Cloud Architecture
Embedded Systems
Enterprise Architecture
Generative Artificial Intelligence (AI)
Lifecycle Management
Machine Learning (ML)
Natural Language
Machine Learning Operations (ML Ops)
IT Management
Natural Language Processing
Privacy
Microsoft Azure
Leadership
Evaluation
Google Cloud Platform
Kubernetes
Use Cases
Software Architecture
Workflow
Technical Drafting
TOGAF

Data Flow
Collaboration
Design Review
Finance
Database
Banking
API
Cloud Architecture
Embedded Systems
Enterprise Architecture
Generative Artificial Intelligence (AI)
Lifecycle Management
Machine Learning (ML)
Natural Language
Machine Learning Operations (ML Ops)
IT Management
Natural Language Processing
Privacy
Microsoft Azure
Leadership
Evaluation
Google Cloud Platform
Kubernetes
Use Cases
Software Architecture
Workflow
Technical Drafting
TOGAF

Summary

Sr AI Architect ( Finance Technology AI Enablement)
Duration: 3- 6 Months (Contract to perm)
Pay: 65/HR
Work Mode: Remote
Interview Type: Not Mentioned

Ropes Test: Yes
Location:

Scottsdale, Arizona 85260

About the Role:

We are looking for a Senior AI Architect who will serve as the top AI/ML technical authority for the finance IT organization—someone who can translate a business transformation vision into a coherent AI/ML technical strategy, design the end-to-end architecture that makes that strategy real, and guide engineering teams through detailed design and implementation.

This is a highly senior, hands-on architecture role. You will operate at multiple altitudes: shaping multi-year AI/ML roadmaps with business and technology leaders, producing detailed reference architectures and design standards, and working directly with engineers to solve hard design problems. You will be the primary architectural voice for GenAI, machine learning, automation, and agentic systems across finance technology.

What You'll Do

Strategy & Vision

Strategy & Roadmapping: Define the AI/ML technical strategy that underpins the finance organization's broader business transformation vision.
Executive Partnership: Partner with business leaders and senior stakeholders to translate financial and operational goals into actionable AI/ML and automation initiatives.
AI-First Philosophy: Establish and evangelize an "AI-first" architectural philosophy across finance technology—identifying where GenAI, ML, and automation should be embedded by design rather than bolted on.
Trusted Advisory: Act as a trusted advisor to business and technology executives on AI/ML capability, feasibility, risk, and value.

Architecture & Roadmap

High-Level Design: Create high-level automation and AI/ML architecture designs and multi-year technology roadmaps aligned to business priorities.
Reusable Frameworks: Architect AI/ML foundational frameworks and platforms that can be reused across multiple finance use cases (fraud detection, forecasting, reconciliation, reporting, analytics, Intelligent document/content/Audio Processing, and beyond).
Advanced Semantic Layers: Design high-performing, complex semantic layers using advanced techniques such as RAG, Knowledge Graphs, and GraphRAG, enabling natural language query against large, complex financial databases with extensive table relationships.
Agentic Workflows: Define reference architectures for agentic AI workflows, including multi-agent orchestration, tool use, memory, and human-in-the-loop patterns for finance process automation.
Governance & Standards: Set architecture and design standards, frameworks, and best practices for AI/ML solution delivery across the organization.

Detailed Design & Engineering Guidance

Blueprint Creation: Produce detailed architecture designs—data flows, integration patterns, model serving, event-driven pipelines, security, and governance controls—that engineering teams can build against.
Engineering Mentorship: Guide and mentor engineers through detailed technical design decisions, code/design reviews, and solution build-out.
Performance & Scalability: Own architectural quality, scalability, and performance for high-volume financial data processing and analytics pipelines.
Platform Evaluation: Evaluate and select tools, platforms, and frameworks (cloud-native and third-party) to support GenAI, ML, and automation initiatives.

Delivery & Governance

Compliance & Governance: Ensure solutions meet enterprise, regulatory, and financial-data governance requirements (data privacy, model risk, auditability, explainability).
MLOps / LLMOps: Drive adoption of MLOps/LLMOps practices for model lifecycle management, monitoring, and continuous improvement.
Design Authority: Represent AI/ML architecture in design authority / architecture review forums and champion consistent standards across teams.

What You'll Bring

Experience

Enterprise Architecture: 12+ years of progressive experience in enterprise architecture, cloud architecture, and distributed systems/platform solutions.
Multi-Cloud Expertise: Proven hands-on experience across major cloud platforms—Azure, Google Cloud Platform, and AWS.
Containerization & Platforms: Deep experience with Kubernetes and container-based platform architecture.
Event-Driven Processing: Strong background in event-driven architectures/frameworks and high-volume, high-throughput data processing systems.
Production GenAI & ML: Demonstrated experience architecting GenAI and Machine Learning solutions in production environments.
Financial Domain: Experience in financial data processing and analytics, ideally within a finance, banking, or FinTech IT organization.
Foundational Frameworks: Track record architecting AI/ML foundational frameworks/platforms used across multiple teams or use cases.

Technical Depth

GenAI: LLM application architecture, prompt/context engineering, RAG, Knowledge Graphs, GraphRAG, semantic search, vector databases.
Agentic AI: Designing and architecting complex multi-step, multi-agent agentic workflows and orchestration patterns.
Machine Learning: Forecasting, fraud detection, anomaly detection, and predictive modeling architectures.
Automation: Business process automation and data processing automation architecture, including intelligent/AI-augmented automation.
Analytics AI: Architecture for AI-enabled analytics and NLP-based querying against large, complex relational data models.
Data & Integration: Large-scale data pipelines, complex database schemas, semantic layer design, API, and event-driven integration patterns.
Cloud & Platform: Azure and Google Cloud Platform AI/ML services (e.g., Azure OpenAI, Azure ML, Vertex AI, BigQuery ML), Kubernetes-based deployment, scalable microservices.

Leadership & Soft Skills

Multi-Level Engagement: Ability to operate credibly at both strategic (executive/business stakeholder) and detailed (engineering) levels.
Stakeholder Influence: Strong stakeholder management and communication skills; able to influence business leaders and technical teams alike.
Standard Setting: Experience setting technical standards, design principles, and best practices at an organizational level.
Technical Mentorship: Strong mentoring and technical leadership skills—comfortable guiding engineers through detailed design and build.
First-Principles Thinking: Structured, first-principles thinker who can bring architectural rigor to ambiguous, transformation-scale problems.

Nice to Have

Prior experience within a Finance Technology, Banking, or regulated financial services environment.
Experience with MLOps/LLMOps tooling and model governance/risk frameworks.
Relevant cloud or architecture certifications (Azure Solutions Architect, Google Cloud Platform Professional Cloud Architect, AWS Solutions Architect, TOGAF, etc.).

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 91172753
Position Id: 9072825
Posted 8 days ago

Company Info

About Trispark Inc

Whether you’re building your dream team or finding your next career move, TriSpark makes it seamless.

𝗧𝗿𝗶𝘀𝗽𝗮𝗿𝗸 𝗜𝗻𝗰. is a Texas, U.S. based powerhouse in 𝗦𝘁𝗮𝗳𝗳𝗶𝗻𝗴, 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁, 𝗜𝗧 𝗖𝗼𝗻𝘀𝘂𝗹𝘁𝗶𝗻𝗴, and Emerging Technology Solutions, with a strong global delivery capability. We are proud to be 𝘁𝗿𝘂𝘀𝘁𝗲𝗱 𝗯𝘆 𝗼𝘃𝗲𝗿 𝟵𝟬+ 𝗙𝗼𝗿𝘁𝘂𝗻𝗲 𝟱𝟬𝟬 𝗰𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀, state agencies, and enterprise clients who count on us for precision, agility, and innovation.

We specialize in 𝗜𝗧 𝗮𝗻𝗱 𝗡𝗼𝗻-𝗜𝗧 𝗵𝗶𝗿𝗶𝗻𝗴, delivering permanent, contract, and SOW-based talent across verticals such as 𝗛𝗲𝗮𝗹𝘁𝗵𝗰𝗮𝗿𝗲, 𝗕𝗙𝗦𝗜, 𝗣𝗵𝗮𝗿𝗺𝗮, 𝗮𝗻𝗱 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆. As a reliable partner in 𝗩𝗠𝗦/𝗠𝗦𝗣 𝗲𝗰𝗼𝘀𝘆𝘀𝘁𝗲𝗺𝘀, we consistently deliver high-quality talent while maintaining strict SLA and compliance standards.

At Trispark, we go beyond traditional outsourcing by enabling 𝗖𝗿𝗼𝘀𝘀-𝗯𝗼𝗿𝗱𝗲𝗿 𝗪𝗼𝗿𝗸𝗳𝗼𝗿𝗰𝗲 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀 providing high-performing distributed teams that drive business success across time zones and borders.

Go to company profile

Fitment

Dice Job Match Score™

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Contact the job poster

Raghvendra Lakhnot

Recruiter @ Trispark Inc

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Sr. Technical manager (Only W2)

Remote

•

Yesterday

Sr. Technical manager Duration: 3- 6 Months (Contract to perm) Pay: 65/HR Work Mode: Remote Ropes Test: Yes Location: Scottsdale, Arizona 85260 Position Summary:We are seeking a highly experienced Senior Technology Manager to lead the Finance Technology AI Enablement engineering team. In this role, you will be responsible for architecting and building best-in-class AI solutions while enabling business and IT partners in their AI adoption journey. You will provide strategic direction to the en

Easy Apply

Contract

Trispark Inc

Job Details

Skills

Data Flow
Collaboration
Design Review
Finance
Database
Banking
API
Cloud Architecture
Embedded Systems
Enterprise Architecture
Generative Artificial Intelligence (AI)
Lifecycle Management
Machine Learning (ML)
Natural Language
Machine Learning Operations (ML Ops)
IT Management
Natural Language Processing
Privacy
Microsoft Azure
Leadership
Evaluation
Google Cloud Platform
Kubernetes
Use Cases
Software Architecture
Workflow
Technical Drafting
TOGAF

Data Flow
Collaboration
Design Review
Finance
Database
Banking
API
Cloud Architecture
Embedded Systems
Enterprise Architecture
Generative Artificial Intelligence (AI)
Lifecycle Management
Machine Learning (ML)
Natural Language
Machine Learning Operations (ML Ops)
IT Management
Natural Language Processing
Privacy
Microsoft Azure
Leadership
Evaluation
Google Cloud Platform
Kubernetes
Use Cases
Software Architecture
Workflow
Technical Drafting
TOGAF

Summary

Sr AI Architect ( Finance Technology AI Enablement)
Duration: 3- 6 Months (Contract to perm)
Pay: 65/HR
Work Mode: Remote
Interview Type: Not Mentioned

Ropes Test: Yes
Location:

Scottsdale, Arizona 85260

About the Role:

What You'll Do

Strategy & Vision

Strategy & Roadmapping: Define the AI/ML technical strategy that underpins the finance organization's broader business transformation vision.
Executive Partnership: Partner with business leaders and senior stakeholders to translate financial and operational goals into actionable AI/ML and automation initiatives.
AI-First Philosophy: Establish and evangelize an "AI-first" architectural philosophy across finance technology—identifying where GenAI, ML, and automation should be embedded by design rather than bolted on.
Trusted Advisory: Act as a trusted advisor to business and technology executives on AI/ML capability, feasibility, risk, and value.

Architecture & Roadmap

High-Level Design: Create high-level automation and AI/ML architecture designs and multi-year technology roadmaps aligned to business priorities.
Reusable Frameworks: Architect AI/ML foundational frameworks and platforms that can be reused across multiple finance use cases (fraud detection, forecasting, reconciliation, reporting, analytics, Intelligent document/content/Audio Processing, and beyond).
Advanced Semantic Layers: Design high-performing, complex semantic layers using advanced techniques such as RAG, Knowledge Graphs, and GraphRAG, enabling natural language query against large, complex financial databases with extensive table relationships.
Agentic Workflows: Define reference architectures for agentic AI workflows, including multi-agent orchestration, tool use, memory, and human-in-the-loop patterns for finance process automation.
Governance & Standards: Set architecture and design standards, frameworks, and best practices for AI/ML solution delivery across the organization.

Detailed Design & Engineering Guidance

Blueprint Creation: Produce detailed architecture designs—data flows, integration patterns, model serving, event-driven pipelines, security, and governance controls—that engineering teams can build against.
Engineering Mentorship: Guide and mentor engineers through detailed technical design decisions, code/design reviews, and solution build-out.
Performance & Scalability: Own architectural quality, scalability, and performance for high-volume financial data processing and analytics pipelines.
Platform Evaluation: Evaluate and select tools, platforms, and frameworks (cloud-native and third-party) to support GenAI, ML, and automation initiatives.

Delivery & Governance

Compliance & Governance: Ensure solutions meet enterprise, regulatory, and financial-data governance requirements (data privacy, model risk, auditability, explainability).
MLOps / LLMOps: Drive adoption of MLOps/LLMOps practices for model lifecycle management, monitoring, and continuous improvement.
Design Authority: Represent AI/ML architecture in design authority / architecture review forums and champion consistent standards across teams.

What You'll Bring

Experience

Enterprise Architecture: 12+ years of progressive experience in enterprise architecture, cloud architecture, and distributed systems/platform solutions.
Multi-Cloud Expertise: Proven hands-on experience across major cloud platforms—Azure, Google Cloud Platform, and AWS.
Containerization & Platforms: Deep experience with Kubernetes and container-based platform architecture.
Event-Driven Processing: Strong background in event-driven architectures/frameworks and high-volume, high-throughput data processing systems.
Production GenAI & ML: Demonstrated experience architecting GenAI and Machine Learning solutions in production environments.
Financial Domain: Experience in financial data processing and analytics, ideally within a finance, banking, or FinTech IT organization.
Foundational Frameworks: Track record architecting AI/ML foundational frameworks/platforms used across multiple teams or use cases.

Technical Depth

GenAI: LLM application architecture, prompt/context engineering, RAG, Knowledge Graphs, GraphRAG, semantic search, vector databases.
Agentic AI: Designing and architecting complex multi-step, multi-agent agentic workflows and orchestration patterns.
Machine Learning: Forecasting, fraud detection, anomaly detection, and predictive modeling architectures.
Automation: Business process automation and data processing automation architecture, including intelligent/AI-augmented automation.
Analytics AI: Architecture for AI-enabled analytics and NLP-based querying against large, complex relational data models.
Data & Integration: Large-scale data pipelines, complex database schemas, semantic layer design, API, and event-driven integration patterns.
Cloud & Platform: Azure and Google Cloud Platform AI/ML services (e.g., Azure OpenAI, Azure ML, Vertex AI, BigQuery ML), Kubernetes-based deployment, scalable microservices.

Leadership & Soft Skills

Multi-Level Engagement: Ability to operate credibly at both strategic (executive/business stakeholder) and detailed (engineering) levels.
Stakeholder Influence: Strong stakeholder management and communication skills; able to influence business leaders and technical teams alike.
Standard Setting: Experience setting technical standards, design principles, and best practices at an organizational level.
Technical Mentorship: Strong mentoring and technical leadership skills—comfortable guiding engineers through detailed design and build.
First-Principles Thinking: Structured, first-principles thinker who can bring architectural rigor to ambiguous, transformation-scale problems.

Nice to Have

Prior experience within a Finance Technology, Banking, or regulated financial services environment.
Experience with MLOps/LLMOps tooling and model governance/risk frameworks.
Relevant cloud or architecture certifications (Azure Solutions Architect, Google Cloud Platform Professional Cloud Architect, AWS Solutions Architect, TOGAF, etc.).

Dice Id: 91172753
Position Id: 9072825
Posted 8 days ago

Company Info

About Trispark Inc

Whether you’re building your dream team or finding your next career move, TriSpark makes it seamless.

Go to company profile

Fitment

Dice Job Match Score™

🔢 Crunching numbers...

Contact the job poster

Raghvendra Lakhnot

Recruiter @ Trispark Inc

View Profile

Create job alert

Never miss an opportunity! Create an alert based on the job you applied for.

Similar Jobs

Sr. Technical manager (Only W2)

Remote

•

Yesterday

Easy Apply

Contract