Description

Solution Design & Architecture

· Lead solution design for complex, cross-functional data and AI problems — from initial discovery through to technical blueprint

· Define and communicate architecture decisions, trade-offs, and delivery approaches to both technical and non-technical audiences

· Design scalable, modular systems that balance the need for speed with enterprise standards for reliability, security, and maintainability

· Participate in architecture reviews, ensuring alignment with enterprise patterns and platform standards

· Create clear technical documentation: architecture diagrams, data flow maps, API contracts, and solution briefs

Rapid Prototyping & Solution Delivery

· Design and deliver working prototypes for complex data and AI problems within compressed timeframes, often days to weeks

· Translate ambiguous business requirements into concrete technical solutions with minimal hand-holding

· Balance speed of delivery with enterprise standards — your prototypes are production-ready, not throwaway

· Continuously iterate on solutions based on direct feedback from product managers, program leads, and end users

· Develop intuitive front-end interfaces and dashboards that bring data and AI outputs to life for business users

· Apply strong UX instincts to simplify complex flows and make agent outputs accessible and actionable for non-technical stakeholders

AI Agent Development

· Design, build, and deploy AI agents and multi-agent systems that automate complex workflows end-to-end

· Develop and maintain agent skills — discrete, reusable capabilities that compose into larger agentic pipelines

· Implement and extend Model Context Protocol (MCP) servers and clients to connect AI agents with enterprise tools, APIs, and data sources

· Design evaluation harnesses, guardrails, and monitoring pipelines to ensure agent reliability and safety in production

· Stay current with the rapidly evolving agentic AI landscape and proactively introduce new techniques and tooling to the team

· Integrate LLMs, RAG systems, and ML models into production workflows

Collaboration & Stakeholder Engagement

· Embed directly with product, program, and engineering teams to co-define problems and co-deliver solutions

· Influence technical direction and build alignment across teams without relying on formal authority

· Communicate complex technical concepts clearly to non-technical business stakeholders — in writing, in meetings, and in executive presentations

· Mentor and elevate junior engineers, sharing patterns and practices for agentic development, prompt design, and rapid delivery

· Foster a collaborative, low-ego team culture where speed and quality go hand in hand

Key Skills

Education

Bachelor's degree