Role Description Build and optimize ETL pipelines for large-scale AI applications, integrating APIs, web scraping, and real-time data processing. Develop and maintain scalable AI data infrastructure using PySpark, Pandas, SQL, and cloud services (Azure, AWS, GCP). Implement retrieval-augmented generation (RAG) pipelines using FAISS, ChromaDB, and Pinecone for AI-driven insights. Deploy and monitor AI applications using FastAPI, Streamlit, Docker, for real-time performance. Work with cross-functional teams to ensure data security, compliance, and AI model reliability in production environments. Qualifications - Bachelor's or Master's degree in Computer Science, Data Engineering, Artificial Intelligence, or a related field. - At least 2-4 years of experience in data engineering, AI/ML, or cloud-based AI infrastructure. - Expertise in Python, PySpark, and SQL for data transformation and large-scale processing. - Experience with cloud platforms (AWS, Azure, GCP) for AI model deployment and data pipeline automation. - Hands-on experience with vector databases (FAISS, ChromaDB, Pinecone) for efficient data retrieval. - Proficiency in containerization and orchestration tools like Docker and Kubernetes. - Strong understanding of retrieval-augmented generation (RAG) and real-time AI model deployment. - Knowledge of API development and AI service integration using FastAPI and Streamlit/Dash. - Ability to optimize AI-driven automation processes and ensure model efficiency. - Strong analytical and problem-solving skills. - Excellent communication and collaboration abilities. Requirements - Expertise in Python, PySpark, and SQL for data transformation and large-scale processing. - Experience with cloud platforms (AWS, Azure, GCP) for AI model deployment and data pipeline automation. - Hands-on experience with vector databases (FAISS, ChromaDB, Pinecone) for efficient data retrieval. - Proficiency in containerization and orchestration tools like Docker and Kubernetes. - Strong understanding of retrieval-augmented generation (RAG) and real-time AI model deployment. - Knowledge of API development and AI service integration using FastAPI and Streamlit/Dash. - Ability to optimize AI-driven automation processes and ensure model efficiency. - Strong analytical and problem-solving skills. - Excellent communication and collaboration abilities. Company Description

• Design, develop, and maintain scalable ETL/ELT data pipelines. • Build and optimize data architectures and warehouses (e.g., Snowflake, BigQuery Etc). • Integrate data from a wide variety of sources using APIs and web browser automations. • Collaborate with company leadership to understand data needs and implement ongoing improvements in system processes. • Monitor and ensure data quality, reliability, and performance. • Automate data workflows and implement data validation and testing processes. • Maintain up-to-date documentation for data pipelines, systems, and processes.

• Fine-tuning of SLMs tailored to specific needs • Implementation of agents and integrations as required • Implementation of multi-LLM routing • Preparation of technical and business documentation • Knowledge transfer • Conduct cost–benefit analysis.

Role Description Fuse Energy is a forward-thinking renewable energy startup on a mission to deliver a terawatt of renewable energy – fast. We're combining first-principles thinking with cutting-edge technology to build a radically better energy system. - Lead data center from early-stage opportunity through Ready-to-Build and energisation - Assess sites from technical, planning, power, and infrastructure perspectives - Develop grid connection and power strategies with National Grid, DNOs, and utility providers - Support planning, permitting, and stakeholder engagement processes - Identify and mitigate technical and development risks - Ensure projects are deliverable, scalable, and aligned with construction requirements - Experience developing data centers or large-scale infrastructure projects - Strong technical understanding of data center infrastructure, including power, cooling, and utility systems, with the ability to evaluate engineering decisions and challenge technical assumptions - Strong understanding of AUS planning and grid connection processes - Experience taking projects from early-stage development through design, permitting, and delivery readiness - Highly analytical, self-directed, and comfortable with significant ownership Qualifications - Experience developing data centers or large-scale infrastructure projects - Strong technical understanding of data center infrastructure, including power, cooling, and utility systems - Strong understanding of AUS planning and grid connection processes - Experience taking projects from early-stage development through design, permitting, and delivery readiness - Highly analytical, self-directed, and comfortable with significant ownership Requirements - Lead data center from early-stage opportunity through Ready-to-Build and energisation - Assess sites from technical, planning, power, and infrastructure perspectives - Develop grid connection and power strategies with National Grid, DNOs, and utility providers - Support planning, permitting, and stakeholder engagement processes - Identify and mitigate technical and development risks - Ensure projects are deliverable, scalable, and aligned with construction requirements Benefits - Competitive salary - Biannual bonus scheme - Fully expensed tech to match your needs