Solution Architect

ROLE OVERVIEW

We are seeking a seasoned Solution Architect to lead the design and delivery of enterprise-grade AI Agent and integration solutions. This role sits at the intersection of AI strategy and enterprise systems engineering — translating complex business requirements into scalable, governed, and observable agentic architectures. You will work closely with product, data, and engineering teams to define blueprints that power next-generation AI capabilities across our fintech platform.

KEY RESPONSIBILITIES

• • Architect end-to-end AI Agent solutions leveraging LLM and Agentic frameworks (LangChain, AutoGen, CrewAI) integrated with enterprise systems.
    • Design API-first and event-driven integration architectures ensuring reliability, scalability, and low-latency across services.
    • Define governance frameworks for AI agents including access control, audit trails, policy enforcement, and responsible AI guardrails.
    • Establish observability standards using LaunchDarkly, feature flagging strategies, and DevOps pipelines for AI-driven systems.
    • Collaborate with stakeholders across Engineering, Data, Product, and Risk to align architecture decisions with business outcomes.
    • Create and maintain Technical Solution Architecture documentation, including architecture decision records (ADRs), data flows, and system diagrams.
    • Evaluate and recommend emerging AI tools, LLM providers, and orchestration platforms for enterprise adoption.
    • Provide technical leadership and mentoring to engineering squads implementing agentic solutions.

REQUIRED SKILLS & EXPERIENCE

• • 8+ years of Solution Architecture or Technical Architecture experience in enterprise environments.
    • Deep expertise in AI Agent Architecture and Large Language Model (LLM) ecosystems.
    • Hands-on experience with Agentic Frameworks — LangChain, AutoGen, CrewAI, or equivalent.
    • Strong background in Enterprise Integration Architecture: RESTful APIs, event-driven systems (Kafka, Event Grid), microservices.
    • Proficiency with observability tooling and feature flagging platforms, including LaunchDarkly.
    • Demonstrated ability to design AI governance and policy frameworks in regulated industries.
    • Experience in financial services, fintech, or banking environments preferred.
    • Excellent communication skills with the ability to present complex architectures to executive and technical audiences.

PREFERRED QUALIFICATIONS

• • Cloud architecture certifications (AWS, Azure, GCP) with AI/ML specialization.
    • Experience with MLOps tooling, model registries, and LLMOps pipelines.
    • Familiarity with compliance frameworks: SOC2, FFIEC, model risk management (SR 11-7).
    • Prior experience contributing to enterprise AI Centers of Excellence (CoE).