Senior Data Engineer

Role Overview

• Drive 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 and Critical Design Reviews (CDRs), ensuring alignment with enterprise patterns and platform standards
• Create clear technical documentation: architecture diagrams, data flow maps, API contracts, and solution briefs
• Design and deliver working prototypes for complex data and AI problems within compressed timeframes, often days to weeks
• Bring genuine curiosity to every engagement — deeply understanding the business case, problem context, and constraints before converging on a solution
• 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
• 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 MCP (Model Context Protocol) servers and clients to connect AI agents with enterprise tools, APIs, and data sources
• Build agent orchestration layers using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or Semantic Kernel
• 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
• Build and deploy AI-powered features and pipelines that automate workflows, surface insights, and enhance decision-making
• Design and implement scalable data pipelines, APIs, and backend services that serve both internal tools and customer-facing products
• Integrate LLMs, RAG systems, and ML models into production data workflows
• Own data modeling, transformation, and quality across the solutions you deliver
• Embed directly with product, program, and engineering teams to co-define problems and co-deliver solutions
• Contribute to technical direction and help build alignment across teams through strong communication and collaboration
• Communicate complex technical concepts clearly to non-technical business stakeholders — in writing, in meetings, and in presentations
• Support and mentor 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.

Requirements

• 4+ years of professional software or data engineering experience, including hands-on solution design and architecture contributions
• Experience designing and delivering end-to-end data and AI systems — from requirements through deployment — with clear documentation and stakeholder communication
• Hands-on experience building AI agents, including defining agent skills, tool use, memory, and multi-step reasoning
• Working knowledge of MCP (Model Context Protocol) — including building or consuming MCP servers to connect agents with external systems
• Experience with agentic frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or Semantic Kernel
• Strong hands-on experience with data engineering: pipelines, ETL/ELT, data modeling, SQL and NoSQL databases
• Proficiency in Python
• Experience with cloud platforms (AWS, Azure, or GCP) and modern data stack tooling
• Exceptional communication and interpersonal skills — you can earn trust quickly, navigate ambiguity, and drive alignment across diverse teams
• Comfort working in fast-paced environments with shifting priorities and high ownership expectations.

Tech Stack

• AWS
• Azure
• Cloud
• ETL
• Google Cloud Platform
• NoSQL
• Python
• SQL

Benefits

• 401(k) plan with matching company contributions
• Comprehensive Medical, Dental & Vision Care
• Paid parental leave at 100% of salary
• Paid Time Off and Company Holidays
• Early access to earned wages through Daily Pay