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Do you want to apply your expertise to a company that truly values its team and that’s working to protect the planet? A company where collaboration, learning and trust are key pieces of the culture? Consider joining us!
ABOUT DUNSKY
Dunsky supports leading organizations across North America in accelerating the transition to a clean-energy future. Through our work in energy efficiency, electrification, renewable energy, climate planning, and net-zero strategies, we help clients develop practical, evidence-based solutions to today's most pressing energy and climate challenges.
Dunsky is looking for a Data & AI Engineer to help build the next wave of AI, data, and modeling capabilities that support how we work, how we use our knowledge, and how we deliver value to clients.
This is a hands-on engineering role at the intersection of applied AI, data engineering, and software development . You will help build AI-powered applications and agents, strengthen the data foundations that support them, and help turn analytical models into reliable, scalable software.
We are looking for a versatile builder who is comfortable working across AI, data, APIs, cloud infrastructure and application development. You will work as part of a cross-functional team including the AI program, software/data engineering resources, IT security and systems, and subject-matter experts across the firm.
KEY RESPONSIBLIITIES
Build practical AI applications and agents
Design and develop LLM-powered applications, agents and automated workflows.
Build solutions using RAG, search, embeddings, structured outputs, tool calling and agentic workflows.
Develop reusable APIs, services and integrations that connect AI systems to Dunsky's data and knowledge.
Prototype quickly with users and help move successful solutions into production.
Build our data and modeling foundation
Design, build and maintain data pipelines, integrations, data models and data lake architecture using Azure and Databricks.
Integrate structured and unstructured data from APIs, business systems, databases, and documents.
Improve data and modeling workflows with a focus on performance and scalability.
Establish appropriate data quality, lineage, metadata, access controls and governance.
Engineer solutions for production
Implement testing, monitoring and evaluation for AI systems, including quality, reliability, latency and cost.
Use Git, CI/CD and modern software development practices.
Incorporate security, privacy, Responsible AI and human oversight into solution design.
Help establish practical standards for AI and data architecture, development, documentation and quality.
Work closely with the business
Partner with consultants and subject-matter experts to translate business needs into practical technical solutions.
Help users understand what AI can and cannot reliably do.
Support discovery, prototyping and testing with internal and client-facing use cases.
Explain technical trade-offs clearly to both technical and non-technical colleagues.
Success in this role means building useful, reliable and reusable AI capabilities on a strong data foundation. You will help us move promising AI ideas into dependable tools, make our data and knowledge easier to use, create reusable building blocks, and deploy solutions with the appropriate quality, security and governance.
IDEAL CANDIDATE
Required skills and experience:
Approximately 3+ years of combined experience in applied AI, data engineering, software engineering, or a related field.
Hands-on experience building applications using LLMs or generative AI APIs .
Practical understanding of RAG, embeddings, vector search, structured outputs, tool/function calling and AI agents.
Strong proficiency in Python and SQL .
Experience with Databricks and the Microsoft Azure ecosystem.
Experience building production data pipelines, integrations, APIs and analytical models.
Ability to work independently, navigate ambiguity…