Director of AI & Automation Software Engineering

CliftonLarsonAllen LLP

Atlanta (GA)

Presencial

USD 180 000 - 240 000

Tempo integral

Há 3 dias

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Resumo da oferta

CLA is a top ten national professional services firm delivering software solutions within our AI & Automation practice. The Software Engineering Director leads architecture, drives client engagements, and mentors engineers while embracing AI-assisted development to deliver secure, reliable software.

This role combines hands-on engineering with strategic design to solve complex business problems in Azure, Power Platform, and automation contexts.

Qualificações

6 years of relevant experience required; 7 years preferred in software engineering, solution architecture, cloud engineering, application development, systems integration, or related technology roles.
Bachelor's degree is required. Combination of relevant experience, education, and training may be accepted in lieu of degree.
3 or more years of experience providing technical leadership across software engineering teams, complex implementations, solution architecture, or software development initiatives.
Strong hands‑on software engineering background with demonstrated experience designing, developing, integrating, deploying, and supporting production applications.
Deep understanding of software architecture, APIs, databases, integration patterns, cloud infrastructure, identity and access management, and distributed systems.
Experience with AI‑assisted development tools, coding agents, or AI‑enabled engineering workflows, coupled with an understanding of how to validate their outputs for correctness, security, and maintainability.
Strong client‑facing communication skills, including technical discovery, requirements clarification, solution presentations, expectation management, and explaining technical tradeoffs to executive and business audiences.
Experience working in consulting, professional services, or other client‑facing environments where technical decisions must account for business outcomes, budgets, timelines, and changing requirements.
Working knowledge of Git, CI/CD, DevOps, automated testing, code review, secure development practices, deployment, monitoring, and production support.
Ability to guide and mentor engineers, provide constructive technical feedback, and improve engineering practices through shared knowledge and practical standards.
Experience working across different technology stacks, including unfamiliar or client‑managed environments.

Responsabilidades

Lead the technical architecture and implementation of client solutions involving custom software, cloud applications, APIs, enterprise integrations, automation, and AI-enabled capabilities.
Work directly with clients to understand their business processes, existing systems, technical constraints, and desired outcomes; translate conversations into practical designs and implementation approaches.
Serve as a trusted technical advisor to clients, communicating architectural decisions, tradeoffs, project risks, and technical recommendations in ways that stakeholders can understand.
Maintain hands-on involvement in software engineering, including architecture, prototyping, code reviews, complex integrations, troubleshooting, and resolving difficult technical challenges.
Evaluate solution approaches across custom development, Microsoft Azure, Power Platform, automation tools, existing enterprise platforms, and hybrid architectures; recommend simplest effective approach based on requirements, security, cost, and maintainability.
Translate business requirements into technical scopes, implementation plans, estimates, dependencies, and acceptance criteria; identify technical risks early and communicate them clearly.
Provide technical leadership across engineering engagements, helping developers work through architectural questions and implementation challenges.
Establish and maintain practical engineering standards for software architecture, coding, testing, security, CI/CD, deployment, documentation, and production support.
Guide implementation in client‑owned environments, accounting for existing infrastructure, security requirements, identity management, data access, deployment processes, and operational constraints.
Apply AI-assisted development tools to accelerate software development, testing, debugging, and documentation while ensuring appropriate technical review and quality control.
Collaborate with software engineers, Microsoft platform engineers, AI engineers, data scientists, product teams, and client technology teams to deliver integrated solutions.
Mentor engineers, share technical knowledge, and help strengthen the team's ability to independently design, build, troubleshoot, and support complex solutions.
Identify opportunities to improve engineering efficiency through reusable architecture patterns, development practices, automation, and lessons learned from client engagements.