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.

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.

Solution Architect

Key skills