Senior Python Engineer – MCP Connector Architecture

About the Company AGM Tech Solutions is a Women-Minority owned IT consulting firm focused on high-impact placements for enterprise and mid-market clients. We build relationships based on trust, integrity, and deep understanding of both client needs and candidate expertise. About the Role Our enterprise client is assembling a specialized team to architect and build Model Context Protocol (MCP) connectors—the critical infrastructure enabling AI agents to interact with enterprise data platforms at scale. This is foundational work: you'll be designing the connector layer that powers the next generation of agentic AI systems. Responsibilities • Architect and implement MCP connectors for enterprise data platforms (Databricks, Snowflake as initial targets) • Build robust Python services and libraries that form the connector framework • Design authentication flows, API integrations, and data access patterns for AI agent consumption • Shape early-stage architecture decisions while maintaining production code quality • Establish testing strategies, CI/CD pipelines, and deployment infrastructure • Collaborate directly with AI/ML teams on connector behavior, agent requirements, and platform evolution Qualifications • Deep Python expertise (3–5+ years building production systems, not just scripting) • Hands-on MCP experience (~1+ year working directly with Model Context Protocol) • Production engineering mindset: you've shipped Python applications that run at scale • Strong MCP fundamentals: understanding of protocol semantics, lifecycle management, and agent interaction patterns • FastMCP library experience (or similar MCP tooling) • Independent execution: you own problems end-to-end and deliver without hand-holding • Experience with REST APIs, OAuth/authentication flows, and third-party integrations • Working knowledge of SQL (Postgres preferred), CI/CD, and Git workflows Required Skills • Machine Learning background: experience with model development, training pipelines, or ML infrastructure • LLM experience: hands-on work building, fine-tuning, or deploying large language models • GenAI development: proven track record building generative AI applications, RAG systems, or agent architectures • MCP expertise: direct experience with Model Context Protocol in production contexts Preferred Skills • ML/GenAI depth: model training, LLM fine-tuning, prompt engineering, embedding pipelines • Prior work building connectors/integrations for Databricks, Snowflake, or similar data platforms • Experience with RAG architectures, vector databases, or semantic search systems • Background in agentic AI systems, LangChain/LlamaIndex, or agent orchestration frameworks • Understanding of LLM observability, evaluation frameworks, or model serving infrastructure • Experience with large-scale integration platforms or multi-connector ecosystems Pay range and compensation package Compensation: Competitive market rate + comprehensive benefits (medical, dental, vision) Equal Opportunity Statement We are committed to diversity and inclusivity in our hiring practices. Logistics • Location: Alpharetta, GA (Hybrid – minimum 2 days/week onsite for architecture discussions and collaboration) • Engagement: Long-term contract • Start timeline: Immediate (critical POC deadline) To apply Submit your resume highlighting: • ML/LLM/GenAI project work (if applicable—strongly preferred) • Specific MCP implementations and production deployments • Python systems you've architected and shipped • Any experience with data platform integrations or GenAI infrastructure Two paths forward: ML/GenAI + MCP experience (highest priority) OR strong Python + strong MCP (still encouraged to apply)