Lead development of a generative AI proof-of-concept and integrate AI solutions into software workflows. Mentor data engineers, design and implement Python-based generative AI applications, build scalable data pipelines, deploy models/APIs, and translate stakeholder requirements into technical solutions while staying current on AI and data engineering best practices.
Key Responsibilities:
- Lead the creation of a POC for using generative AI in software development, demonstrating its potential to improve efficiency, quality, and innovation.
- Collaborate with software development teams to integrate generative AI solutions into existing workflows.
- Lead and mentor a team of data engineers, providing technical guidance and fostering a collaborative team environment.
- Design, develop, and implement generative AI applications using Python.
- Work closely with stakeholders to understand business requirements and translate them into technical solutions.
- Drive the development and execution of data engineering strategies to support business objectives.
- Develop and maintain scalable data pipelines, API and model deployments, and workflows.
- Communicate complex analytical findings and insights to non-technical stakeholders in a clear and concise manner.
- Stay current with industry trends, best practices, and emerging technologies in data analytics, generative AI, and Python programming.
Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.
- 5+ years of experience in data engineering and AI, with at least 2 years in a leadership or supervisory role.
- Proficiency in Python programming and its libraries (e.g. pandas, numpy, scikit-learn, matplotlib, seaborn).
- Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and their data analytics and AI services.
- Strong understanding of statistical analysis, machine learning, and data mining techniques.
- Experience with generative AI models (e.g., GPT, GANs) and their applications in software development.
- Experience with big data technologies (e.g., Hadoop, Spark) and data visualization tools (e.g., Tableau, Power BI) is a plus.
- Solid experience with SQL and database management.
- Excellent problem-solving skills and the ability to work independently and as part of a team.
- Strong communication and interpersonal skills, with the ability to effectively convey technical concepts to non-technical stakeholders.
Preferred Qualifications:
- Knowledge of data governance and data privacy regulations.
- Experience in agile development methodologies.
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What you need to know about the Seattle Tech Scene
Home to tech titans like Microsoft and Amazon, Seattle punches far above its weight in innovation. But its surrounding mountains, sprinkled with world-famous hiking trails and climbing routes, make the city a destination for outdoorsy types as well. Established as a logging town before shifting to shipbuilding and logistics, the Emerald City is now known for its contributions to aerospace, software, biotech and cloud computing. And its status as a thriving tech ecosystem is attracting out-of-town companies looking to establish new tech and engineering hubs.
Key Facts About Seattle Tech
- Number of Tech Workers: 287,000; 13% of overall workforce (2024 CompTIA survey)
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- Funding Landscape: $3.1 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Madrona, Fuse, Tola, Maveron
- Research Centers and Universities: University of Washington, Seattle University, Seattle Pacific University, Allen Institute for Brain Science, Bill & Melinda Gates Foundation, Seattle Children’s Research Institute
