Identify opportunities and develop AI solutions to improve the efficiency and effectiveness of business processes. Build and configure agents that reason, plan, and act using models, tools, and data, aligned to approved patterns by leveraging tools such as Databricks Apps, Databricks Agents, Power BI, GenAI, and AI  

Rapidly prototype new AI capabilities while adhering to standards that enable promotion to enterprise-grade deployments

Implement use-case workflows end-to-end. Translate business and operational requirements into AI workflows spanning data ingestion, inference, tool execution, and human-in-the-loop review

Optimize performance and cost. Tune prompts, models, and agent interactions to improve accuracy, latency, and cost efficiency

Maintain GitHub repositories and development practices. Manage repository structure, branching, pull requests, code reviews, and documentation to support secure, collaborative, and repeatable AI solution delivery

Collaborate with business teams to embed digital tools into planning and reporting while ensuring alignment with the business priorities

Provide technical guidance and training on digital tools

Analyze large datasets to identify anomalies, trends and control gaps

Stay current with emerging technologies and developments in AI governance and risk management

Apply responsible AI guardrails. Embed safety controls, validation steps, and explainability mechanisms into agent logic and prompts by design

• Bachelor’s degree is required, preferably in Computer Science, Information Systems, Engineering, Business or a related field. An advanced degree or certification is a plus

• Relevant work experience in AI, data analytics, and/or digital transformation within a corporate or consulting environment and at least 6 months of substantial use of AI coding assistants is strongly preferred

• Proficiency in Python and AI frameworks for LLMs and agents

• Experience with prompt engineering, evaluation techniques, and structured outputs

• Familiarity with vector databases, embeddings, and retrieval-augmented generation (RAG) patterns 

• Working knowledge of API integration and tool execution within agent workflows

• Exposure to CI/CD, model deployment, and observability concepts

• Experience using GitHub repositories for source control, collaboration, version management, and code review within enterprise development workflows

• Proven experience with one or more of the following: SQL, Python, Databricks, AI, GenAI, and Azure

• Pragmatic judgment about where AI should and should not be leveraged

• Strong analytical skills with emphasis on data-driven decision making and troubleshooting

• PROFESSIONAL SKILLS

• Professional oral and written communication skills with ability to translate complex technical concepts and explain AI behavior/limitations to non-technical stakeholders and influence skills to encourage adoption

• Ability to collaborate with stakeholders to understand diverse automation needs and advocate for unified solutions

• Ability to build relationships and work in a team atmosphere as well as work independently with self-confidence

• Effective time management skills with the ability to adapt to changing demands, multi-task, and manage competing priorities. Ability to effectively organize tasks, meet schedules, and deliver on customer commitments

• Ability to communicate progress, problems, and best practices to management, leaders, and teammates