Data Engineer

Job Overview

As a Forward Deployed Data Engineer, you will embed with product, program, and engineering teams to rapidly design, architect, prototype, and deploy data-driven solutions that solve high-priority business problems. You will move from concept to prototype in days, maintaining enterprise-grade standards for quality, security, and scalability.

• Lead solution design for complex, cross-functional data and AI problems, from discovery through technical blueprint.
• Define and communicate architecture decisions, trade-offs, and delivery approaches to technical and non-technical audiences.
• Design scalable, modular systems balancing speed with enterprise standards for reliability, security, and maintainability.
• Participate in architecture reviews and Critical Design Reviews (CDRs) to ensure 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 time frames.
• Balance speed of delivery with enterprise standards; prototypes are production-ready.
• Continuously iterate on solutions based on 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 Lang Chain, Lang Graph, Auto Gen, CrewAI, or Semantic Kernel.
• Design evaluation harnesses, guardrails, and monitoring pipelines to ensure agent reliability and safety in production.
• 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 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.
• Influence technical direction and build alignment across teams without formal authority.
• Communicate complex technical concepts clearly to non-technical business stakeholders in writing, meetings, and 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.

• Required
• 6+ years of professional software or data engineering experience, including solution design and architecture ownership.
• Demonstrated ability to architect end-to-end data and AI systems—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) to build or consume MCP servers connecting agents with external systems.
• Experience with agentic frameworks such as Lang Chain, Lang Graph, Auto Gen, CrewAI, or Semantic Kernel.
• Strong hands-on experience with data engineering: pipelines, ETL/ELT, data modeling, SQL and No
  
  SQL databases.
• Proficiency in Python.
• Experience with cloud platforms (AWS, Azure, or GCP) and modern data stack tooling.
• Exceptional communication and interpersonal skills; earn trust quickly, navigate ambiguity, and drive alignment.
• Comfort in fast-paced environments with shifting priorities and high ownership expectations.
• Preferred
• Experience with RAG architectures, vector databases (Pinecone, Weaviate, pgvector), semantic search, and building indexing systems and data processing pipelines.
• Familiarity with prompt engineering, fine-tuning, and LLM evaluation techniques.
• Experience with agent observability and tracing tools (Lang Smith, Arize, Weights &…