Role overview
About The Role
We are seeking a hands-on AI Engineer to help design, build, and deploy intelligent features within our application ecosystem. This role will collaborate closely with our Manager of Data Science & AI Engineering to identify opportunities for generative AI, predictive analytics, and automation across business workflows.
You will be responsible for scoping, prototyping, and implementing AI products — from model design to integration — leveraging both proprietary data and leading cloud AI platforms.
What you'll work on
- Partner with the Manager of Data Science & AI Engineering to scope and deliver AI-driven product features and internal tools.
- Design and implement machine learning and generative AI solutions using cloud services such as AWS Bedrock, SageMaker, and Amazon Q in QuickSight.
- Integrate AI services into web and application layers (e.g., via REST APIs, LangChain, or Bedrock SDK).
- Develop proof-of-concepts for natural language querying, document summarization, forecasting, and user experience enhancements using AI.
- Work with structured and unstructured data stored in AWS RDS, SQL Server, and other data sources.
- Collaborate with data engineering and analytics teams using tools like Power BI, QuickSight, and Python-based data pipelines.
- Ensure responsible AI design, including model monitoring, bias testing, and performance validation.
- Stay current with emerging technologies in AI (LLMs, vector databases, RAG architectures, and MLOps best practices).
What we're looking for
- Experience deploying chatbots, retrieval-augmented generation (RAG), or embedding-based search.
- Demonstrated experience in applying AI complex domains with large numbers of entities and relationships
- Proven track record in building AI applications for end-users
- Experience validating the performance of AI applications and incrementally improving accuracy
- Knowledge of API integration and orchestration frameworks (FastAPI, Flask, or Streamlit).
- Understanding of responsible AI principles and data governance best practices.
- Experience integrating AI with BI or analytics dashboards for end-user insights.
Tech Stack You’ll Work With
- Languages: Python, SQL, JSON
- Cloud: AWS (Bedrock, SageMaker, Lambda, RDS, S3, Glue)
- Databases: AWS RDS, SQL Server
- Analytics: Power BI, QuickSight with Q
- AI/ML Tools: LangChain, Bedrock SDK, PyTorch, scikit-learn, Hugging Face Transformers
Tags & focus areas
Used for matching and alerts on DevFound Fulltime Ai Machine Learning Deep Learning Data Science Nlp Mlops Generative Ai Pytorch Tensorflow