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Design and own the full production lifecycle of sovereign AI systems for international governments, ensuring reliability, security, and real-time observability of LLM-based applications.
Build and maintain high-performance data pipelines that bridge operational technology (OT) systems like SCADA and IoT sensors with cloud analytics in the oil and gas sector, using Azure, Python, and Spark.
Design and build enterprise-grade AI systems using RAG, agentic workflows, and cloud platforms for HR and finance domains.
Build and improve AI-powered business solutions, cloud platforms, and automation tools using full-stack web development, LLMs, and secure enterprise systems.
Lead a hybrid role managing data engineering teams and client projects, designing Azure-based cloud data platforms and GenAI-ready data architectures for banking, insurance, and retail clients.
Design and implement end-to-end AI solutions using Python, PySpark, Databricks, Postgres and open-source LLMs like Qwen, building data pipelines, RAG systems and AI agents for enterprise clients.
Build and run the data backbone that ingests trillions of events daily, maintaining Kafka, ClickHouse, Aurora, and MongoDB on AWS to keep Nexthink’s platform reliable and fast.
Build and maintain data pipelines and AI solutions on Google Cloud Platform, integrating LLMs and automating workflows for cybersecurity projects.
Build and maintain data pipelines and ETL workflows in Python, orchestrating data ingestion from multiple sources for AI-driven fintech analytics and RAG systems.
Build and maintain ETL pipelines, optimize MongoDB schemas, and create Metabase dashboards to power AI-driven travel rental analytics and reporting.
Lead backend engineering for an AI-native HR platform, building agentic systems that automate hiring, onboarding, and employee operations using Python, LLMs, and conversational AI.
Build and maintain production-grade AI agents that automate HR workflows using Python, LLMs, and full-stack tooling to ensure reliability, cost-efficiency, and scalability in enterprise environments.
Architect and build a full-stack AI platform in TypeScript/React that unifies hardware engineering workflows, with hands-on coding and technical leadership in an early-stage startup.
Build and scale AI-driven products using LLMs, RAG pipelines, and vector databases with Rust or Golang, from prototype to production in rapid cycles.
Build and maintain Python-based APIs and backend services for an AI company, using FastAPI/Django/Flask, async programming, and cloud tools like AWS/Azure.
Design and scale real-time data pipelines for AI systems, focusing on RAG, vector databases, and semantic layers to power agentic reasoning in enterprise environments.
Build real-time data pipelines and vector databases to power AI agents, transforming enterprise logs into embeddings for RAG systems with automated quality guardrails.
Build robust data pipelines and ML/GenAI solutions for Swiss clients, from ETL to dashboards and predictive models, using Python, SQL, Azure, and Power BI.
Build Java/Spring Boot backends and transition into data/AI engineering, designing data pipelines, AI workflows, and cloud-native systems for clients in banking, government, retail, and transportation.
Senior back-end developer building scalable AI-powered marketing automation systems in a FinTech company, using Go, Node.js, Python, and cloud services.
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