Jobs at 4M Analytics

Lead the founding U.S. forward-deployed engineering function by building and deploying production software for utility customers. Work directly with field crews and operations teams, integrate enterprise and GIS systems, translate field insights into scalable product capabilities, and make architecture decisions amid ambiguity. Mentor engineers, establish the growing U.S. team, and collaborate closely with the Israel-based R&D organization. The hybrid Austin role includes regular customer and field-site travel and several annual trips to Israel.

The role involves building HR programs, supporting HR processes, partnering with managers on talent development, and optimizing HR infrastructure in a fast-paced tech environment.

Manage the full customer lifecycle for public sector accounts, from onboarding through renewal. Build relationships across government organizations, drive adoption and retention, identify expansion opportunities, handle escalations, and advocate for customer needs. Use AI, BI tools, and data analysis to monitor account health and inform account strategies. The role requires executive communication, change management, cross-functional collaboration, and up to 80% travel for on-site customer engagement.

Lead backend and GIS software development for subsurface utility mapping. Design Python applications, ETL workflows, databases, data infrastructure, and CI/CD pipelines for processing, testing, monitoring, and maintaining geospatial data quality. Collaborate with product, design, and QA teams, provide technical guidance, review third-party technologies, optimize systems, and address technical debt. The role requires strong Python, GIS, PostgreSQL, AWS, orchestration, containerization, and debugging experience within an AI-first engineering culture.

Own onboarding, adoption, and renewals for a portfolio of AEC enterprise accounts. Build executive and project-level relationships, track account health and usage, identify expansion opportunities, lead implementations, and feed customer insights into product and sales strategy to protect and grow ARR.

Lead research and production implementation of computer vision and algorithmic solutions, own end-to-end model quality and deployment, design experiments, monitor production health, mentor team members, and integrate AI-augmented workflows while collaborating with data engineering and product teams.

Build and maintain distributed data pipelines (SQS, Airflow, Kubernetes), integrate ML outputs into ETL workflows, contribute to shared Python libraries, debug multi-service pipelines, improve observability, and manage ETL/data infrastructure and database operations for large-scale datasets.