Womble Bond Dickinson
AI Engineer
- Compensation
- $90.5K–$122K
- Location
- Atlanta, Georgia, United States
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 1+ years
- Category
- Ai engineering
- Posted
Skills
Must have
- A bachelor's degree in computer science, software engineering, or a related technical field, or an equivalent combination of education, training, and experience, is required.
- Hands-on experience with large language model APIs and agent frameworks, including prompt design, retrieval-augmented generation, tool use, and evaluation, is required.
- Experience with process mapping, workflow documentation, and process measurement is preferred.
- Experience in a law firm or professional services environment, including familiarity with document management systems, is helpful but not required.
- One or more years of professional experience in AI engineering, software engineering, machine learning, data engineering, or a related technical discipline. This should include designing, building, an
- Hands-on experience building and deploying software or AI-powered solutions.
- Experience working with one or more modern AI/ML platforms, APIs, or large language models.
- Proficiency in at least one programming language such as Python, JavaScript/TypeScript, Java, C#, or similar.
- Understanding of software development principles, APIs, databases, version control, testing, and deployment.
- Ability to take a problem or requirement and develop a practical technical solution.
- Strong analytical and problem-solving skills.
- Ability to work effectively in a fast-moving environment where requirements may evolve.
- Document work clearly enough that another engineer can reproduce, maintain, or audit it.
- Handle confidential client and firm information with discretion and in accordance with firm policy.
- Communicate clearly in writing and in presentations to both technical and non-technical audiences.
- Exercise sound judgment and work independently with minimal supervision in a remote setting.
- Work collaboratively with attorneys, paralegals, professional staff, and technology teams.
Full description
Womble Bond Dickinson (US) LLP is seeking an AI Engineer to join their Technology team. The AI Engineer will design, develop, and deploy AI-powered applications, agents, and automation solutions. The role combines software engineering and applied AI/ML to turn business requirements into reliable, scalable technology. The AI Engineer will work across the full development lifecycle, from understanding requirements and designing technical solutions through to development, testing, deployment, monitoring, and ongoing improvement. The role also supports the extension of firm-built solutions to enterprise clients and offers a defined path toward forward-deployed, client-facing engineering work.
RESPONSIBILITIES: AI Solutions
- Design, develop, test, and maintain AI-powered applications, agents, and automation solutions.
- Build custom AI solutions, including process automation, workflow, and cost-reduction use cases, from requirements through to deployment.
- Develop AI-enabled applications, APIs, and backend services, and integrate them with existing firm systems and data sources.
- Evaluate business requirements and recommend an appropriate technical and AI approach, including platform selection.
- Build and integrate solutions using AI and cloud platforms such as OpenAI, Claude, Azure AI Foundry, and Microsoft Copilot.
- Implement testing, monitoring, and error handling across applications and AI systems to support reliable production operations.
- Design and run evaluations of model and agent outputs, including accuracy, quality, and safety testing, and implement guardrails and human review controls appropriate to each use case.
- Apply the firm's AI governance, security, data governance, and confidentiality standards when handling sensitive firm and client data.
- Document solutions, architecture, and design decisions to ensure maintainability and reuse.
- Participate in sprint planning, architectural discussions, and code reviews, and use Git and Azure DevOps for version control and release management.
- Collaborate with attorneys, department leaders, and other stakeholders to gather requirements, and explain technical decisions and AI behavior to non-technical audiences.
- Extend solutions to large enterprise clients, partnering with a project manager or engagement manager on client-facing delivery.
- Contribute to the team’s capability through cross-training and knowledge sharing, and grow over time into more forward-deployed, client-facing engineering work.
Business Process Automation
- Analyze department and firm-wide information workflows to identify manual, repetitive, or high-volume steps suitable for automation.