Engineer IV - Applied AI

JOB SUMMARY

Responsible for designing, developing, implementing, and supporting AI-powered solutions that address business challenges and create operational efficiencies across the organization. Leverages existing large language models (LLMs), retrieval-augmented generation (RAG) architectures, agentic workflows, data platforms, and software engineering practices to develop scalable solutions that enhance business processes, customer experiences, and decision-making capabilities. Partners closely with business stakeholders, product teams, and technology teams to identify opportunities, translate business needs into technical solutions, and deliver production-ready AI applications and services.

ESSENTIAL DUTIES AND RESPONSIBILITIES

AI Solution Design & Development

• Design, develop, implement, and support AI-powered applications and services utilizing large language models (LLMs), agentic workflows, prompt engineering techniques, APIs, and retrieval-augmented generation (RAG) architectures.  

• Evaluate business requirements and translate complex or ambiguous business problems into scalable technical solutions.  

• Research, evaluate, prototype, and recommend AI technologies, tools, platforms, and vendors to support business objectives.  

• Design and develop conversational AI solutions, chatbots, virtual assistants, and intelligent workflow automation capabilities.  

Data Integration & Engineering

• Develop and maintain integrations between AI solutions, enterprise applications, APIs, databases, and cloud data platforms.  

• Query, transform, structure, and manage data to support AI and machine learning solutions utilizing platforms such as Snowflake and related technologies.  

• Develop and maintain retrieval pipelines, semantic search capabilities, vector databases, and data services supporting AI-enabled solutions.  

• Ensure data quality, security, governance, and performance requirements are met within assigned solutions.

Solution Delivery & Operational Support

• Deploy, monitor, maintain, and optimize AI solutions in production environments.  

• Monitor application performance, reliability, utilization, and operating costs and implement improvements as appropriate.  

• Troubleshoot application, integration, and data issues and provide timely resolution to support business operations.

• Create and maintain technical documentation, solution architecture diagrams, standards, and support materials.

Business Partnership & Innovation

• Partner with business stakeholders, product teams, and technology teams to identify opportunities for AI adoption and process automation.  

• Provide technical leadership and subject matter expertise related to applied AI technologies and emerging industry trends.

• Support pilot programs, proofs of concept, and innovation initiatives that advance organizational capabilities.

• Promote adoption of AI-enabled solutions through training, knowledge transfer, and stakeholder engagement.  

Continuous Improvement

• Stay current with developments in artificial intelligence, machine learning, software engineering, and data technologies.

• Continuously evaluate solution effectiveness and recommend enhancements to improve business value, quality, scalability, reliability, and user experience.

• Participate in architecture reviews, code reviews, and development best practices to ensure high-quality solution delivery.

MANAGEMENT & SUPERVISORY RESPONSIBILTIES

• Typically reports to an Engineering Manager, Director of Engineering, Director of AI, or other technology leadership position. 

• Functions as a senior-level individual contributor.

• May provide technical leadership, mentoring, and guidance to engineers, analysts, and project teams.

• No direct supervisory responsibility.

JOB QUALIFICATIONS: Education & Experience Requirements

Education

• Bachelor's degree in Computer Science, Engineering, Data Science, Mathematics, Information Technology, or related field required.

• Master's degree preferred.

• Equivalent combination of education, training, and experience may be considered.  

Experience

• Minimum of 7 years of progressive software engineering, data engineering, artificial intelligence, machine learning, or related technology experience.  

• Minimum of 3 years of experience designing, building, and deploying AI-enabled solutions within production environments.  

• Experience developing applications using LLMs, AI APIs, prompt engineering, retrieval-augmented generation (RAG), and agentic workflow technologies.  

• Experience with Python development, APIs, integrations, and cloud-based technologies.  

• Experience working with Snowflake, SQL, data transformation, and enterprise data platforms.  

• Experience implementing and supporting AI applications using modern frameworks and orchestration tools.  

• Strong analytical, problem-solving, organizational, and communication skills.  

• Experience leading technical initiatives and influencing cross-functional teams preferred.