Lead Software Engineer – AI & Cloud Data Engineering (Contingent)

Locations: Irving, TX (preferred) | Charlotte, NC | Phoenix, AZ | Minneapolis, MN | San Antonio, TX | Des Moines, IA | New Jersey | California
Work Type: Contingent (Conversion Eligible)

About the Role

We’re building a modern, AI-enabled data platform that supports large-scale analytics and automation in a complex, hybrid-cloud environment. As a Lead Software Engineer – AI & Cloud Data Engineering, you will play a critical role in designing, building, and operationalizing cloud-native data and AI solutions that support next-generation analytics and security use cases.

You will work in a fast-paced, highly collaborative environment alongside principal engineers, product managers, and data engineers to deliver scalable data pipelines and AI-driven automation capabilities. This is a visible, hands-on technical leadership role with meaningful impact across a large data ecosystem.

Responsibilities

In this role, you will:

• Lead the design and implementation of cloud-native, AI-enabled data pipelines on Google Cloud to ingest, transform, and distribute large-scale data.
• Build and operate streaming and batch data processing solutions using technologies such as Kafka, Spark, and Flink.
• Apply AI and agentic frameworks (e.g., LangChain, LangGraph, RAG/GraphRAG) to automate data management, governance, quality, metadata, and compliance workflows.
• Consult on complex, large-scale data engineering initiatives, contributing to architectural decisions and long-term platform strategy.
• Collaborate strategically within a matrixed organization, partnering with engineers, product managers, and stakeholders to roadmap and deliver high-priority data capabilities.
• Drive adoption of modern data and AI technologies through technical leadership, mentorship, and hands-on development.
• Support the migration of on-premises data platforms to Google Cloud–based architectures.
• Ensure solutions align with organizational standards, security requirements, and compliance expectations.

Minimum Qualifications

• 5+ years of experience in software or data engineering, or equivalent experience gained through work, consulting, education, military service, or training.
• Experience working in large-scale data environments.
• Hands-on experience building and supporting cloud data solutions, including Spark-based ingestion and processing.
• Strong proficiency in Python and experience with Kafka.
• Demonstrated experience developing data pipelines on Google Cloud, including services such as:
  • Google Cloud Storage
  • BigQuery
  • Dataproc
  • Cloud Composer (Airflow)
• Experience with data lakehouse architectures and modern data processing patterns.
• Proven ability to work on complex, ambiguous technical problems requiring in-depth analysis and sound judgment.

Preferred Qualifications

• Recent, hands-on experience with AI tooling and frameworks, including:
  • LangChain
  • LangGraph / ADK
  • Agentic frameworks
  • Retrieval-Augmented Generation (RAG) and GraphRAG
  • MCP-based agent architectures
• Experience using AI to accelerate data engineering, including code generation, context engineering, and prompt engineering.
• Hands-on experience with streaming technologies (Kafka, Flink, Spark Streaming).
• Strong background in cloud-based data lakes and warehouses with automated data pipelines.
• Public cloud certifications (e.g., GCP Professional Data Engineer, Azure Data Engineer, AWS Data Analytics Specialty).
• Experience with web-based UI development (React, Node.js) a plus.

Why This Role

• Opportunity to build a modern AI-powered data platform from the ground up
• High-impact work with visibility across engineering and product teams
• Exposure to cutting-edge AI, data engineering, and cloud-native technologies
• Collaborative environment that values innovation, technical excellence, and continuous learning

Apply now