Top Tech Jobs & Startup Jobs in Atlanta, GA

Owns computer vision systems end to end, from roadside camera configuration and image quality through model development, edge inference, production deployment, monitoring, and customer outcomes. Builds detection, tracking, OCR, attribute extraction, embedding, and re-identification systems; optimizes pipelines for constrained edge hardware; investigates field failures; improves datasets and evaluation frameworks; and collaborates with engineering and field teams to deliver reliable roadside intelligence at scale.

Supports fund operations, investment accounting, portfolio reporting, transaction reconciliations, capital calls, treasury management, investor reporting, fund valuations, NAV calculations, audits, tax reporting, and process improvements for alternative investment clients.

Own the Hi-Vis scaffold management platform’s product vision, strategy, roadmap, and lifecycle. Translate customer and market insights into prioritized initiatives, lead development through launch, and drive adoption, retention, and commercial growth. Collaborate with Product, Technology, Sales, Marketing, and Customer Success teams while using data, automation, and AI-enabled solutions to improve platform value and industry outcomes.

Own the vulnerability management pipeline for a cloud-based hospitality SaaS platform. Responsibilities include maintaining Tenable and CrowdStrike Falcon scan coverage, prioritizing and validating vulnerabilities, automating scan-to-ticket workflows with Python and Jira, coordinating remediation, tracking SLAs, reporting program health, and supporting security incident response on-call rotations.

Design and govern the future-state enterprise data platform for the Medical Stop Loss business using Microsoft Fabric and Azure. Responsibilities include data architecture, dimensional and physical modeling, ingestion and integration patterns, data governance, quality, security, lineage, semantic models, and analytics enablement. The role guides data engineering and BI teams, modernizes legacy platforms, supports cloud migrations, and collaborates with business and technology stakeholders across regulated insurance operations.

Early-career Data Engineering Analyst supporting AIG’s Data Office through a rotational program. Responsibilities include developing cloud-based data pipelines, collecting and transforming data, building modern software systems, and supporting analytics and data science use cases. The role emphasizes data quality, security, compliance, collaboration, analytical problem-solving, and professional development through mentoring, masterclasses, and on-the-job experiences.

Design, develop, test, operate, and maintain backend-driven mobile products and SDK integrations. Write production-ready code, perform failure analysis, conduct code reviews, ensure compliance and security, apply DevOps and SRE practices, collaborate in Agile teams, and support high-scale distributed systems and monitoring.

Leads enterprise engineering technology strategy and lifecycle ownership, including evaluation, deployment, governance, support, vendor coordination, training, and continuous improvement. Advises stakeholders on engineering software, cloud solutions, digital delivery, integrations, and emerging technologies. Develops workflows, standards, documentation, and adoption plans while resolving technical issues and influencing modernization and investment decisions. Requires extensive transportation-project technology experience, strong OpenRoads Designer and ProjectWise expertise, AEC digital-delivery knowledge, and demonstrated mentoring and cross-functional collaboration.

Own the end-to-end property damage claims product, including self-service workflows, AI agents, integrations, and user experiences for claimants, law firms, case managers, and automotive partners. Conduct user research, prototype solutions, write requirements, partner with engineering, manage launches, define metrics, and establish product processes as the company scales.

Designs and maintains scalable, low-latency data pipelines for real-time and batch market data. Builds ETL/ELT processes, optimizes storage and streaming systems, supports productionizing AI and machine-learning models, and improves data quality, observability, reliability, and cost efficiency. Collaborates with data scientists, ML engineers, and product teams to evolve Fetcherr’s data platform.