AI Solution Architect

Type: Full-Time

Role Overview

We are seeking an experienced solution architect to take ownership of our core product architecture and drive its next evolutionary phase: embedding native AI capabilities. In this role, you will be responsible for maintaining, scaling, and enhancing our core software platform while designing and implementing Model Context Protocol (MCP) connections, tool-calling frameworks, and autonomous AI agents directly into the product core.
You will bridge traditional software engineering with cutting-edge AI architectureturning our existing product into an intelligent, context-aware, and agent-driven platform.

Key Responsibilities

Core Product Development & Enhancement

• Maintain & Scale the Core Platform: Take full technical ownership of the primary codebase, ensuring high performance, reliability, security, and scalability as the product grows.
• Feature Engineering & Architecture: Design and build core product features, refactoring existing systems where necessary to support seamless AI integration and modular updates.
• API & System Architecture: Refine backend architectures, database schemas, and external API interfaces to support low-latency interactions and high-throughput data processing.

AI Feature Integration & Modernization

• Model Context Protocol (MCP) Implementation: Expose internal product data, services, and APIs via custom MCP servers, enabling LLMs and AI agents to securely query product context and execute actions.
• Agentic AI & Automation Integration: Embed autonomous AI agents and tool-calling capabilities inside the product to automate complex user workflows and decision-making tasks.
• Context & Memory Management: Design robust state-management, long-term memory systems, and context-window optimization to ensure AI responses are accurate and grounded in real-time product data.

Required Qualifications

Professional Experience

• 8+ years of full-stack or backend software engineering experience building and maintaining production-grade SaaS platforms or products.

Core Technical Skills

• Core Software Engineering: Mastery of modern backend languages (Python/Go) and modern web architectures.
• AI & Agentic Frameworks: Proven experience with agent orchestration frameworks (e.g., LangGraph, AutoGen, CrewAI, LlamaIndex Agents) and function-calling paradigms.
• Model Context Protocol (MCP): Solid understanding of MCP standards, including building custom MCP servers and client integrations for dynamic context access.
• Data & Databases: Strong expertise with relational (PostgreSQL, MySQL) and non-relational databases, caching mechanisms (Redis), and vector databases/indexes.
• APIs & Integration: Deep understanding of RESTful APIs, WebSockets, gRPC, and asynchronous event-driven architectures.

Preferred Qualifications

• Experience refactoring legacy codebases to adopt modern AI/LLM plugin structures.
• Familiarity with LLM observability and monitoring tools (e.g., LangSmith, Phoenix, Arize) to track latency, costs, and execution accuracy.
• Knowledge of cloud platforms (AWS, Azure, or GCP) and containerization (Docker, Kubernetes).

Key Personal Traits

• Product Mindset: You write code with the end-user experience and business objectives top of mind, not just technical complexity.
• Pragmatic Innovator: Ability to balance shipping stable core product features with experimenting on bleeding-edge AI architecture.
• Autonomous Ownership: Thrives in taking end-to-end responsibility for a featurefrom technical spec to production deployment.