AI & Automation Engineer
Dadavidson
| Company | Dadavidson |
| Category | Engineering |
| Location | Minneapolis |
| Remote | On-site (inferred) |
| Employment | Full-time |
| Level | Not stated |
| Salary | USD 90k–120k |
| Posted | 27 Jan 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (lever) |
Description
D.A. Davidson Companies is an independent, employee-owned company with a rich history spanning 90 years. We are dedicated to conducting our business in accordance with the highest standards of integrity and ethics, and delivering outstanding service to our clients and each other. We support a friendly, open and supportive culture, and encourage candid communication and productive engagement that make our companies and each of us better. Just as we work to improve our clients’ financial well-being, we also work to strengthen local communities—and giving back is one of our core values. You can learn more about our company culture and impact in our latest annual report.
Summary/Function:
We are seeking a Mid-Level AI and Automation Engineer to develop next-generation AI capabilities within our Microsoft-based environment. This role will focus on building intelligent assistants and automated workflows using tools like Microsoft 365 Copilot Studio, Power Automate, and Azure AI Foundry. The ideal candidate will combine software engineering expertise with a passion for leveraging AI to transform business processes in a financial services and wealth management domain. You will work on integrating large language model solutions into enterprise systems, ensuring they are secure, compliant, and deliver real value to end-users.
Qualifications:
• Education & Experience: Bachelor’s degree in Computer Science, Software Engineering, or related field. 5+ years of experience in software development, automation engineering, or similar roles.
• Microsoft Ecosystem Proficiency: Hands-on experience with Microsoft Power Automate and related Power Platform tools for workflow automation. Familiarity with M365 Copilot features or similar AI bot/agent development tools (e.g. Azure AI services, cognitive services).
• Programming Skills: Proficiency in at least one programming or scripting language (such as Python, C#, or JavaScript) to extend and customize solutions. Experience building or consuming RESTful APIs and working with data integration.
• Cloud & AI Knowledge: Working knowledge of Azure cloud services and AI/ML frameworks. Ability to deploy applications or automations in a cloud environment and integrate AI APIs (Azure OpenAI, Azure Cognitive Services, etc.).
• DevOps Mindset: Experience with version control (git and Bitbucket) and continuous integration/continuous deployment (CI/CD) pipelines for software projects. Comfortable using tools like Azure DevOps or GitHub Actions to automate build-test-deploy processes.
• Problem-Solving & Communication: Strong analytical and problem-solving skills with a track record of delivering solutions that meet business needs. Excellent communication skills to work effectively with both technical and non-technical team members.
• Coordination: Align efforts with other lines-of-business and functional areas, such as our partners in Operations, Finance, Wealth Management, and more.
Preferred Qualifications:
• Copilot Studio Expertise: Experience with Microsoft 365 Copilot Studio – for example, having built or managed AI copilots/agents in a production setting. Knowledge of designing conversation flows, topics, tools, and using Copilot’s advanced features (custom actions, agent-to-agent workflows).
• Advanced AI & ML Skills: Familiarity with large language models beyond basic API usage – e.g., experience with prompt tuning, deploying LLMs, or implementing retrieval-augmented generation (RAG) pipelines with vector databases for domain-specific Q&A. Experience with Azure AI Foundry and Azure AI capabilities like document intelligence, computer vision, speech, and more.
• Financial Services Experience: Background in financial services or wealth management technology projects. Understanding of industry regulatory requirements (e.g. data privacy, audit, model risk management) and how to design AI solutions that comply with them.
• Security & Compliance Focus: hands-on exp
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