AI and Data Engineer
Employment Info
JOB DETAILS
Requirements
- AI and data engineering experience, including hands-on delivery of working applications
- Practical experience building with large language models in production settings
- Experience working with or developing AI connectors, preferably connectors that retrieve information from complex systems
- Demonstrated capability developing data pipelines between systems, preferably using Microsoft Fabric and/or Data Build Tool (DBT)
- Experience with large language model application patterns such as prompting, retrieval-augmented generation, embeddings, vector databases, tool use, function calling, and evaluation
- Agentic engineering capability: able to use coding agents such as Claude Code, Codex, or similar tools to accelerate software delivery, including task scoping, prompt design, code review, testing, debugging, and integrating agent-generated changes into a maintainable codebase
- Experience designing and building APIs and MCPs
- Good engineering habits: version control, testing, code review, documentation, logging, and secure handling of data
- Evidence of practical AI build work (internal tools, side projects, open-source, demos, prototypes, or shipped products)
- High agency: ability to take unclear problem, shape with users, build working solution, and iterate after release
Responsibilities
- Build internal AI tools that support consulting workflows, including evidence synthesis, proposal review, knowledge retrieval, quality assurance and document production
- Develop and maintain data pipelines that ensure consultants have cutting-edge data available for their projects
- Develop connectors between AI and other systems to enable more effective workflows
- Prototype new AI applications with consulting teams, then use feedback and measurement to decide what should be stopped, improved or scaled
- Maintain production AI tools, including monitoring, bug fixes, user support and iterative improvement
- Integrate LLMs, retrieval systems, APIs, databases, and internal knowledge sources into secure, usable applications
- Contribute to technical choices for Nous’ product portfolio, including build-versus-buy decisions, architecture, deployment patterns, and evaluation methods
- Work with other Nous team members and consulting teams so tools fit Nous’ delivery standards, security requirements, and operating model
Desired Qualifications
- Experience with Azure OpenAI API or AWS Bedrock ecosystems
- Experience with cloud deployment, preferably Azure
- Experience with CI/CD pipelines and infrastructure-as-code
- Experience with Microsoft Fabric and Data Build Tool (DBT)
- Background in management consulting, professional services, or another environment where written judgement and client delivery standards matter
- Experience building tools for knowledge work, document-heavy workflows, research, analysis, or decision support
Are you interested in this position?
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