Distinguished Architect

Job Title: Distinguished Architect

Responsibilities

As Distinguished Architect, you will be responsible for groundbreaking development, integration and support across multiple technological and/or business platforms. The distinguished architect is capable of leading a team of architects and works alongside senior management, software engineers and technologists to ensure the strategic alignment of technological solutions and business objectives. The Distinguished Architect will provide architectural mentorship and oversight across a portfolio of Company Platforms. The Distinguished Architect is capable of prototyping and presenting designs and ideas to an Architecture Review Board and to executive technology and business leadership.

The Distinguished Architect will be responsible for:

• Leading a team of architects; offering guidance, thought leadership and ensuring proper resource allocation in order to deliver top-quality solutions.
• Developing architectural strategy across assigned Company Platforms, ensuring enterprise-level consistency and alignment.
• Establishing and communicating strategy to executive staff, industry partners and customers; using recognized technical and business expertise to influence, guide, and craft business strategy and decision-making at the highest interpersonal levels.
• Providing consultation, design input, technical direction and feedback for consistent Company Platform architectural approaches across portfolio Principal Architects and senior engineering leadership.
• Driving and developing product and solution strategies that inform product requirements and investment decisions for Company Platforms across the organization, weaving the enterprise technology vision into the planning and investment processes.
• Implementing robust controls, governance, and risk management for AI platforms, including data security, privacy, and continuous monitoring, with reference to current and future toolsets and platform capabilities.
• Ensuring platform controls and governance are integrated with durable enterprise architecture principles, enforcing resilience, observability, and compliance across all AI initiatives.

Required Qualifications

• 15+ years of working experience in web-development or solutions architecture, with a proven track record of developing consumer-facing and internal solutions.
• Experience implementing large-scale technological enhancements and/or pivots, including pilot implementation and analysis.
• Excellent understanding of DevOps;terraform and ansible.
• Understanding of multiple programming languages, including at least one front end framework (Angular/React/Vue), such as Python, Java, JavaScript, Ruby, Golang, C, C++, etc.
• Experience working with IT infrastructure and cloud development.
• Experience working with data and DBMS, including legacy and emerging database technologies.
• Experience with RDBMS, NoSQL.
• Experience building highly available customer-facing applications, in a GDHA setting.
• Experience building cloud-native applications.
• Experience with API's.
• Experience designing highly available and resilient solutions; ability to identify performance improvement opportunities and transform traditional monolith architecture to modern microservices-based loosely decoupled architecture.
• A bachelor's degree or foreign equivalent in computer science or a related field.
• Experience in 2 or 3 of the following technology areas: Infrastructure, Security, DevOps, Application Development, Database technologies, Cloud computing (AWS, Azure, GCP).

AI Platform & Technical Skills

Candidates should demonstrate knowledge and hands-on experience across the following enterprise AI architecture competencies:

AI Platform & Model Access

• Designing model consumption patterns (API, AI gateway, vendor managed AI).
• Understanding centralized vs embedded model access.
• Azure OpenAI, AWS Bedrock, provider-embedded AI (Salesforce, ServiceNow, Microsoft co-pilot studio).

AI Platform Architecture & MLOps

• Enterprise RAG architecture patterns; embedding lifecycle management.
• Agentic workflows, vector stores and enterprise capabilities integration.
• AWS SageMaker, Amazon Bedrock Agentcore and similar platforms.
• MLOps/LLMOps (MLFlow): prompt versioning, model registry, model gateway across lifecycle stages.

Agent & Orchestration Frameworks

• Agent vs workflow vs rules-based decisioning; single-agent vs multi-agent orchestration.
• Copilot Studio, Salesforce Agentforce, conceptual LangChain/LangGraph literacy.

Integration & System Interaction

• API-first integration design; read/write boundary enforcement.
• Event-driven vs synchronous execution (Kafka, Event Hub patterns).

Security, Identity, Access & Execution Boundaries

• Service identities for agents; least-privilege and RBAC enforcement.
• Azure Entra ID / AWS IAM patterns; prompt-injection defenses.
• Data leakage prevention, output filtering & moderation, jailbreak detection.
• PII detection and redaction; training data isolation; inference-time controls.

Guardrails & Policy Controls

• Input/output filtering and prompt protection; tool allow-listing and policy-based blocking.
• Platform-native guardrails (Copilot Studio, Bedrock Guardrails).

Observability, Monitoring & Governance

• Prompt, response, and action logging; decision traceability and runtime monitoring.
• SIEM integration and AI observability tooling awareness.
• Agent registry and lifecycle state tracking; change detection and re-classification triggers.
• ServiceNow-based governance workflows.

Cost, Performance & DevOps Delivery

• Token-based cost drivers and usage monitoring; latency vs accuracy trade-offs; quota and budget enforcement mechanisms.
• CI/CD integration for AI components; versioning of prompts, workflows, and agents.
• Safe rollout and environment promotion patterns.

Enterprise Competencies

• Learning Agility:
• Demonstrates the ability to rapidly acquire and apply technical expertise in AI, machine learning, and data platforms; embraces evolving toolsets, programming languages, and frameworks with a growth mindset
• Stays current with industry trends, regulatory developments, and emerging architecture patterns across cloud, AI, and enterprise platforms
• Customer Centricity:
• Puts enterprise and end-user needs at the center of architectural decisions; ensures solutions are reliable, compliant, and aligned with business objectives
• Communicates complex technology strategy effectively to executive stakeholders, industry partners, and customers, building trust through transparency and expertise

• Tenacity / Persistence:
• Guides technologists through rapidly changing environments, removing impediments and driving architectural decisions with conviction even in the face of ambiguity
• Demonstrates persistence in aligning enterprise technology vision with investment processes and delivering high-quality outcomes across large-scale, complex programs

Desired Qualifications

• 5+ years of working experience in the financial services industry
• UI/UX experience, including relevant web/application branding techniques
• Comfortable/experience navigating large corporate structure
• Executive speaking and presentation skills — formal presentations, white-boarding, large and small group presentations
• Familiarity with regulatory requirements and risk management, especially in highly regulated environments such as banking; openness to candidates from other regulated industries such as healthcare and insurance

Education and Certifications

• Required: Bachelor's degree in Software Engineering, Computer Science, Computer Engineering or related discipline
• Preferred: Master's degree in Software Engineering, Computer Science, Engineering, Mathematics or related discipline