Senior AI Engineer

The Senior AI Engineer is responsible for designing developing deploying and continuously improving production AI agents and agentic workflows that support attorneys practice groups and Firmwide Department teams across the Firm. This role translates complex business needs into reliable AI enabled solutions that combine language models enterprise tools governed data workflow automation and appropriate human review. Working primarily within Azure Databricks and/or Azure AI Studio with native Azure services the Senior AI Engineer will develop solutions using technologies such as n8n LangGraph Python and enterprise APIs. The position will maintain a strong hands-on development focus while also providing technical guidance code review mentoring and training to AI Engineers and helping establish engineering standards and best practices. The Senior AI Engineer will partner closely with the department leadership AI Engineers Data Architects DevOps teams and business stakeholders to deliver secure scalable and production ready AI solutions.

KEY RESPONSIBILITIES

• Partner with attorneys practice groups and Firmwide teams to understand existing workflows identify opportunities for AI-enabled solutions and define technical requirements acceptance criteria and appropriate boundaries for automation and human review.
• Design build deploy and maintain production AI agents and agentic workflows using n8n LangGraph Python enterprise APIs and related technologies.
• Develop n8n workflows incorporating triggers webhooks AI Agent nodes enterprise connectors reusable sub-workflows custom code secure credential management and appropriate error handling.
• Build stateful LangGraph workflows incorporating tool calling conditional routing checkpoints persistent state stopping conditions recovery mechanisms and human approval steps.
• Design prompts context assembly structured outputs retrieval-augmented generation (RAG) and model selection strategies based on defined quality latency cost and business requirements.
• Develop reusable agent tools APIs and integrations that enable agents to retrieve information and perform authorized actions securely across enterprise systems.
• Partner with the Data Architect to implement governed and permission-aware data access retrieval persistent state and memory while maintaining source traceability and appropriate user and matter-level access controls.
• Develop evaluation datasets automated tests and regression testing processes in partnership with domain experts to assess agent behavior retrieval quality tool-use accuracy task completion groundedness latency and cost.
• Analyze agent traces tool calls workflow outcomes and failure patterns using evaluation and observability tools to troubleshoot issues and continuously improve solution performance.
• Incorporate appropriate security and reliability controls including input and output validation authorization credential protection retries timeouts stopping conditions recovery procedures and escalation paths.
• Test solutions for risks such as prompt injection inappropriate tool use unauthorized data access and data leakage incorporating human approval for consequential actions where appropriate.
• Partner with DevOps teams to support application deployment environment configuration secrets management monitoring release management observability and rollback processes across Azure environments.
• Maintain ownership of the production performance troubleshooting maintenance and continuous improvement of assigned AI agents and workflows.
• Mentor and train AI Engineers through technical guidance pairing code reviews and practical learning sessions.
• Establish document and promote engineering best practices related to agent architecture workflow development evaluation testing security observability and production delivery.

REQUIRED EDUCATION KNOWLEDGE & EXPERIENCE

Demonstrated experience personally designing developing deploying and supporting production AI agents agentic applications or tool-enabled large language model (LLM) workflows.

Strong Python development skills and working knowledge of SQL APIs automated testing version control code review and maintainable software integration practices.

Hands-on experience with LangGraph or a comparable framework used to develop stateful multi-step AI agents.

Experience with n8n or a comparable workflow automation platform and the ability to develop and support solutions that combine workflow automation with custom agent services.

Hands-on experience delivering AI solutions using Azure Databricks Azure AI Studio and/or native Microsoft Azure services including model access application deployment and integration with governed enterprise data.

Strong understanding of agent architecture and workflow design including tool schemas prompt and context management structured outputs state transitions memory checkpointing stopping conditions and human review.

Experience designing integrations using APIs webhooks and asynchronous execution including authentication rate limits retries error handling and idempotency.

Experience implementing retrieval-augmented generation (RAG) and governed data access including retrieval filtering source permissions citations and validation of retrieved information.

Experience developing evaluation datasets automated tests and regression testing processes and using agent traces and failure analysis to improve solution performance.

Understanding of AI application security and reliability practices including authorization credential protection sensitive information handling constrained tool access recoverable workflows and appropriate human controls.

Experience with production software delivery practices including versioning environment configuration automated testing observability monitoring and rollback procedures.

Demonstrated ability to translate ambiguous or complex business requirements into practical technical solutions and clearly communicate technical considerations and tradeoffs to technical and non-technical stakeholders.

Demonstrated ability to mentor and train other engineers conduct effective code reviews and contribute to technical standards and best practices while maintaining significant hands-on development responsibilities.

PREFERRED SKILLS & KNOWLEDGE

Production experience using both n8n and LangGraph particularly solutions combining workflow automation with custom Python-based agent services.

Experience deploying agents through Azure Databricks and using Lakebase or similar technologies for persistent agent state checkpoints and memory.

Experience with AI evaluation and observability tools such as MLflow LangSmith or comparable platforms.

Experience developing Model Context Protocol (MCP) servers reusable agent tools or integrations connecting AI solutions with enterprise systems and governed data.

Experience with multi-agent architectures model routing advanced retrieval techniques and other agentic design patterns.

Working knowledge of JavaScript or TypeScript for custom integrations and lightweight application interfaces.

Experience developing user interfaces that provide visibility into agent progress source citations approval workflows and user feedback.

Experience delivering AI or technology solutions directly with business users in legal services professional services or other environments involving sensitive information and complex 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 $170000 - $200000. Final 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.

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