Trainee / Junior AI Engineer supporting real customer projects at WE BUILD AI. Working with AI applications including automation solutions and machine learning models in a hybrid environment.
About the role
- Full Stack AI Engineer developing production-grade applications focused on Generative AI and Retrieval-Augmented Generation at Acuity Inc. Collaborating with stakeholders to translate requirements into technical solutions in a hybrid work environment.
Responsibilities
- Build and Deploy GenAI Solutions: Design, develop, and optimize generative AI applications, including RAG pipelines and agentic systems that leverage Large Language Models (LLMs)
- Machine Learning Development: Build and deploy traditional machine learning models using frameworks like XGBoost, Random Forest, and other ML algorithms based on business requirements and use cases
- Full Stack Development: Create end-to-end AI-powered applications using modern frameworks like FastAPI for backend services and React or Streamlit for intuitive user interfaces
- Production AI Systems: Deploy AI models into production environments and build robust systems that monitor performance, automate retraining, and ensure reliability at scale
- Cloud Architecture: Leverage Azure cloud services to build scalable, secure, and cost-effective AI infrastructure
- LLM Integration: Implement advanced LLM capabilities including prompt engineering, embeddings, fine-tuning, and API integrations to create intelligent applications
- Containerization & DevOps: Design and deploy containerized applications using Docker, ensuring consistent and reproducible deployments across environments
- Problem Solving: Identify, analyze, and resolve complex technical challenges, optimizing for performance, scalability, and exceptional user experience
- Cross-Functional Collaboration: Partner closely with product managers, designers, data scientists, and engineers to deliver innovative AI solutions that meet business objectives
- Technical Communication: Translate complex AI and technical concepts into clear, actionable insights for both technical and non-technical stakeholders
Requirements
- Bachelor's degree in Computer Science, Software Engineering, or related technical discipline with 4+ years of proven software development experience, OR Master's degree with 2+ years of experience
- Strong programming skills in Python and Java, with excellent software design and development capabilities
- Hands-on experience with Generative AI and machine learning frameworks (e.g., TensorFlow, PyTorch, LangChain, LlamaIndex)
- Solid understanding of LLM concepts, including embeddings, prompt engineering, fine-tuning, and model evaluation
- Demonstrated experience building RAG (Retrieval-Augmented Generation) systems and agentic architectures
- Experience with Azure cloud services (or similar cloud services) and cloud-native application development
- Proficiency with containerization technologies, particularly Docker
- Experience building APIs and microservices using FastAPI or similar frameworks
- Front-end development experience with React or Streamlit
- Proven track record deploying AI models into production and building automated monitoring and retraining pipelines
- Strong version control skills using Git and collaborative development workflows
- Ability to work effectively in cross-functional teams and communicate technical concepts clearly
- Familiarity with data pipelines, databases (SQL/NoSQL), and ETL/ELT processes
Benefits
- Health care
- Dental coverage
- Vision plans
- 401K benefits
- Commissions/incentive compensation depending on the role
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