Top Engineering Manager Jobs in Atlanta, GA

Leads the Product Acquisition engineering team and drives technology strategy, architecture, software delivery, DevOps maturity, platform adoption, vendor management, and operational excellence. Partners with product managers on roadmaps and business outcomes, ensures engineering standards and production support, and coaches, recruits, and develops engineers and consultants. Requires strong software development, product operating model, project management, stakeholder communication, and technical leadership experience.

Leads end-to-end warehouse, eCommerce, packaging, and distribution solution design from RFI/RFP analysis through implementation handoff. Develops layouts, process models, pricing estimates, automation strategies, ROI analyses, and productivity metrics. Optimizes warehouse flow, storage, material handling, and operational processes while collaborating with sales, marketing, operations, vendors, and customers. Provides technical leadership, mentorship, and engineering best-practice development across the organization.

Leads the Data Platform and Infrastructure team, owning strategy, architecture, execution, and organizational development. Responsibilities include managing and mentoring engineers, guiding data ingestion and platform design, establishing APIs, SLAs, governance, security, monitoring, disaster recovery, and cost optimization. The role partners with Product, Data, Finance, Security, and Analytics teams to enable reporting, experimentation, machine learning, and data products while scaling reliable infrastructure and developing future technical leaders.

Leads and develops a team of software engineers while balancing people management with technical leadership. Responsibilities include coaching, performance management, roadmap planning, architecture and code-quality guidance, hiring, staffing, risk management, incident response, stakeholder communication, and cross-team engineering initiatives. The manager partners with product and engineering leadership to deliver reliable software and foster a collaborative, accountable culture.

Leads and scales the MSP/MSSP engineering team responsible for multi-tenant SaaS platform capabilities, including account hierarchies, tenant isolation, delegated administration, dashboards, licensing, and white-labeling. Oversees architecture, engineering quality, roadmap execution, partner support, hiring, mentoring, and team development. Collaborates with Product, Partnerships, Customer Success, Sales, Finance, and engineering leadership while balancing strategic delivery with operational needs.

Lead a product engineering team to own roadmaps, design scalable cloud-native systems, ship customer-facing features, ensure quality and reliability, hire and mentor engineers, and coordinate cross-functional delivery.

Leads the backend platform engineering team responsible for scalable, reliable, secure core systems. Owns platform strategy, roadmap, architecture, operational excellence, reliability metrics, incident response, and engineering quality standards. Manages, hires, and develops backend engineers while partnering with Product, Security, Customer Operations, and other engineering teams. Establishes guardrails for AI-assisted development and drives platform APIs, shared services, and infrastructure supporting company-wide product delivery.

Lead the SSCS Add-On engineering team to develop security capabilities, managing delivery, team growth, and quality in a collaborative environment.

Lead a 15-person Container Product Engineering team building hardened container images, registry services, build systems, adoption tooling, and compliance features. Own team outcomes, hiring, coaching, roadmap execution, technical quality, delivery, planning, and cross-functional collaboration. Remain hands-on through code and design reviews while guiding AI-native engineering practices. The role partners with product and platform teams and offers a path toward broader Director-level scope.

Leads a team of 10 engineers building and maintaining NIBRS and compliance reporting capabilities for public safety records platforms. Oversees technical quality, validation, certification, delivery, incident follow-through, resource allocation, and team development. Partners with product, R&D, agencies, and regulators to implement federal and state reporting requirements, improve engineering operations, and define the roadmap for new states, report types, automation, and platform capabilities. The role is remote within the United States with travel of up to 25%.

Lead a developer productivity engineering team responsible for CI/CD, build systems, internal tooling, and AI-augmented development workflows. Improve developer experience, engineering velocity, and software quality through scalable infrastructure, productivity metrics, AI tool adoption, coaching, and governance. Partner cross-functionally, mentor engineers, evaluate AI technologies and costs, and establish standards for security, correctness, licensing, and data handling.

Leads a software engineering team building backend services, APIs, and product integrations. Responsibilities include people management, technical direction, architecture reviews, delivery planning, vendor coordination, API and integration standards, testing, observability, security, release readiness, and production support. The manager also recruits and develops engineers, manages dependencies and risks, and ensures reliable, maintainable solutions across internal teams, customers, and external technology partners.

Lead the BMS engineering team to deliver, manage, and optimize BMS platforms across data centers. Oversee design reviews, develop BMS standards (points, graphics, sequences), support commissioning and QC, perform design/operational analysis (e.g., TES sizing, trend analysis), manage project communication, RFIs, and closeout deliverables.

Lead a software engineering team to ensure quality delivery and growth, managing performance and technical leadership while collaborating with product and design.

The Mechanical Engineering Manager leads a project team in the Aviation group, ensuring project completion through technical expertise, resource management, and client relations. Responsibilities include project planning, performance monitoring, and proposal support.

The Engineering Manager will lead and mentor engineering teams, define technical strategies, collaborate with cross-functional teams, and drive project success with a focus on high-quality software delivery.

Leads and grows a distributed software engineering team building a scalable cloud data and analytics platform. Owns architecture, data modeling, technical delivery, roadmaps, product collaboration, agile planning, quality standards, security alignment, vendor relationships, and engineering KPIs. The role remains hands-on with coding, code reviews, documentation, data architecture, deployment, and development of SaaS data products using Azure or AWS, Microsoft Fabric or Snowflake, and Power BI.

Manage and lead electrical design for mission-critical MEP projects: coordinate teams and subcontractors, ensure NEC compliance, resolve design challenges, conduct cross-discipline reviews, report to leadership, and mentor junior staff.

Manage and grow multiple engineering teams (3–5 direct reports, hire 3–5 more), coach engineers to own large, loosely defined projects, provide feedback on specs, occasionally code/debug in the codebase, and lead department-wide initiatives to improve engineering practices (reviews, interviews, demo data, developer experience).

Leads and mentors cross-functional engineering teams building and operating distributed, API-driven, cloud-native platforms. Owns technical strategy, architecture, delivery outcomes, engineering excellence, operational reliability, and API lifecycle governance. Drives Agile, DevOps, cloud migration, observability, and incident management practices. Establishes responsible AI adoption across software development and guides delivery of AI-enabled products, including agentic solutions, with appropriate evaluation and controls.

Manage and grow a product engineering team at a remote cloud cost-management software company. Lead prioritization, delivery, quality standards, recruiting, and cross-functional collaboration with product, design, and leadership. Help engineers ship customer-focused features spanning spend management, interfaces, data pipelines, visualizations, and application performance. Coach engineers, remove blockers, promote ownership, and guide tradeoffs between velocity and quality.

Lead and grow a 10-15 person engineering team building cloud-native, high-volume payment platforms. Provide technical direction, hands-on development (20-30% time), mentor engineers, recruit talent, set product/technical strategy, and drive delivery using modern UI, full-stack, and automation patterns.

Leads DevOps engineering teams and manages cloud infrastructure and foundational services across AWS, GCP, and Azure. Oversees infrastructure as code, Kubernetes, CI/CD pipelines, scalability, reliability, cost optimization, monitoring, troubleshooting, and cloud security. Partners with product, engineering, and security stakeholders while mentoring engineers and driving continuous improvement and modern DevOps practices.

Lead and manage a traffic engineering team delivering traffic forecasts, simulations, safety studies, design plans, and GDOT-compliant deliverables. Oversee schedules, budgets, QA/QC, client coordination, and advance projects through the GDOT Plan Development Process. Mentor junior staff, coordinate multidisciplinary teams and represent AECOM at stakeholder and public meetings.

Leads a quality engineering team while remaining hands-on with AI-powered test automation across API, UI, integration, and end-to-end workflows. Evaluates AI tools, improves test frameworks and regression efficiency, supports release readiness, analyzes defects, tracks quality metrics, and partners with Engineering, Product, DevOps, and Release teams. Coaches employees on AI-native quality practices, prompt engineering, responsible AI use, and evaluating AI-generated tests.