AI Engineer

Nashville Tennessee

Job Description

The AI Engineer is responsible for designing developing testing and deploying AI-enabled solutions that support the Firms legal and business operations. Working directly with attorneys practice groups and Firmwide Department teams this role translates business needs and workflows into practical scalable AI solutions using technologies such as Azure Databricks Microsoft Azure n8n LangGraph and Databricks Agent Bricks. As part of the Firms AI engineering team the AI Engineer will contribute throughout the development lifecycle from discovery and prototyping through production deployment monitoring and continuous improvement. The role will collaborate closely with Senior AI Engineers Data Architects DevOps teams and other technical stakeholders while applying shared engineering standards and best practices. Engineers may bring complementary strengths in areas such as data engineering application and front-end development or applied data science with assignments aligned to individual capabilities development interests and evolving business needs.

KEY RESPONSIBILITIES

• Partner with attorneys practice groups and business teams to identify AI opportunities understand workflows define requirements and establish measurable success criteria.
• Design develop test and deploy AI agents and multi-step workflows using platforms and frameworks such as Azure Databricks n8n LangGraph and Databricks Agent Bricks.
• Integrate AI solutions with enterprise applications APIs governed data sources and native Microsoft Azure services incorporating appropriate human review and approval processes.
• Develop prototypes in collaboration with users and translate successful concepts into reliable scalable production applications.
• Build and maintain evaluation datasets automated tests and quality measures to assess agent behavior retrieval quality tool-use accuracy task completion performance latency and cost.
• Analyze execution traces system behavior and failure patterns to troubleshoot issues and continuously improve AI solutions.
• Collaborate with Data Architecture and DevOps teams to support governed data access application deployment environment configuration monitoring and production support.
• Design AI solutions with appropriate reliability safeguards including error handling retries timeouts stopping conditions recovery processes and controls designed to prevent unintended or duplicate actions.
• Apply security access controls data protections source traceability and responsible AI practices throughout solution design and deployment including protections against prompt injection inappropriate access and data leakage.
• Engage with users following deployment to gather feedback support adoption measure business impact and identify opportunities for continued enhancement.
• Participate in code reviews technical documentation knowledge sharing and the development of reusable components standards and engineering best practices.

REQUIRED EDUCATION KNOWLEDGE & EXPERIENCE

• Strong Python programming skills and demonstrated ability to develop maintainable production-quality software using APIs automated testing version control and code review.
• Working knowledge of SQL and experience integrating application data and AI components.
• Hands-on experience developing AI agents agent-enabled applications or multi-step AI workflows involving language models enterprise information APIs or external tools.
• Experience with prompt and context design structured outputs tool integration state management error handling and human-in-the-loop workflows.
• Practical experience with Azure Databricks and working knowledge of Microsoft Azure services used for application development integration or deployment.
• Understanding of retrieval-augmented generation (RAG) embeddings retrieval techniques and the relationship between source quality and AI system performance.
• Experience evaluating and troubleshooting AI applications including analyzing execution traces failures task completion quality latency or cost.
• Understanding of production engineering practices including application deployment configuration management secrets management monitoring automated testing and troubleshooting.
• Working knowledge of authentication authorization role-based access controls and security considerations associated with enterprise AI applications and sensitive information.
• Strong analytical and problem-solving skills with the ability to translate ambiguous business requirements into practical technical solutions.
• Ability to communicate technical concepts and tradeoffs effectively to both technical and non-technical stakeholders.
• Demonstrated collaboration accountability curiosity and ability to work effectively with engineers domain experts and business users.

PREFERRED SKILLS & KNOWLEDGE

• Experience deploying monitoring and supporting AI applications in a production environment.
• Experience with one or more AI orchestration or workflow technologies including n8n LangGraph Databricks Agent Bricks or comparable platforms.
• Experience with MLflow LangSmith or similar AI tracing observability and evaluation tools.
• Advanced experience with Azure Databricks technologies including Spark Delta Lake Unity Catalog Lakebase or Delta Sharing.
• Experience designing and optimizing RAG solutions including vector search hybrid retrieval filtering reranking document processing metadata extraction and retrieval evaluation.
• Experience with graph databases knowledge graphs graph-based RAG or techniques for identifying and linking entities and relationships across information sources.
• Experience working with PostgreSQL or similar technologies to support persistent agent state checkpoints or memory.
• Front-end or application development experience using TypeScript JavaScript React or similar technologies.
• Experience designing user-facing AI applications incorporating streaming responses citations progress indicators feedback mechanisms and human review.
• Experience developing reusable AI tools and enterprise integrations including Model Context Protocol (MCP) or comparable integration approaches.
• Experience designing evaluation datasets benchmarks regression testing automated scoring or LLM-based evaluation methods.
• Knowledge of statistical analysis or experimental design used to evaluate AI system performance and improvements.
• Experience with Microsoft Entra ID managed identities and enterprise authentication and authorization models.
• Experience working in legal services professional services technical consulting or another environment involving sensitive information and complex business workflows.

PHYSICAL REQUIREMENTS

• Ability to sit and stand for extended periods.

• Ability to lift up to 15 pounds.

The expected salary range for this position is $85000 - $ compensation will be determined based on several factors including but not limited to relevant experience qualifications skill set and geographic location.

Pillsbury Winthrop Shaw Pittman LLP is an Equal Opportunity Employer.

If you require an accommodation in order to apply for a position please contact us at .

Required Experience:

IC