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Backend developer designing and building AI and search-integrated backend services for client projects using C#/.NET, Python, Elasticsearch, and LangGraph/LangChain.
Backend .NET developer embedded at a client site in Rennes, designing and developing backend services integrating AI and search technologies using C#/.NET, Python, SQL, MongoDB, and Elasticsearch.
The Applied AI Engineer will leverage generative AI tools to enhance business analysis, documentation, coding, and research processes. The role requires a quantitative degree and at least two years of experience in data analytics or AI implementation.
Citigroup is seeking a Senior Software Engineer to develop full-stack, cloud-native applications using Java or Python and modern JavaScript frameworks. The role involves building scalable systems with potential exposure to generative AI technologies.
About The Team Shopee will be prioritizing applicants who have a current right to work in Singapore , and do not require Shopee sponsorship of a visa . Kindly note that you can only be considered in one recruitment…
The AI/LLM Engineer will design and develop intelligent applications including chatbots, copilots, and autonomous agents. The role involves orchestrating LLM APIs, building RAG pipelines, and implementing security guardrails using technologies like Python/Node.js, LangChain, and vector databases.
This Senior AI/LLM Engineer role involves designing and building scalable LLM-based applications such as chatbots, copilots, and autonomous agents. The position focuses on RAG pipeline architecture, API orchestration, and ensuring production-grade security and observability using technologies like Python, LangChain, and vector databases.
Lead end-to-end AI initiatives for Emirates Group, designing and deploying ML/AI solutions to improve operations and customer experiences using GenAI, LLMs and optimisation frameworks.
Build and own the AI infrastructure powering Forter’s customer-experience products, integrating LLM agents (AWS Bedrock, LangChain) into scalable backend services and data pipelines.
Builds and maintains production-grade backend services in Node.js/TypeScript, with cross-stack flexibility (including React). Focuses on API design, observability, and LLM agent system architecture, often driving decisions in a small team.
Job Title: Full Stack Developer (AWS / TypeScript / AI) Company: 167 Solutions Location: Bristol (Hybrid) Salary: £40,000 - £70,000 per annum (DOE) Contract Type: Permanent Experience Level: Minimum 3 years'…
Backend developer building scalable Java/Spring Boot services and APIs for UK government digital projects, with a focus on integrating agentic AI (LLM agents, RAG) into the engineering platform.
Builds and maintains scalable Java/Spring Boot backend services and APIs for UK government projects, integrating agentic AI workflows (LLMs, tool-use, RAG) into production systems while ensuring security and observability.
Lead a team building AI-driven marketing analytics and automation tools, including conversational agents and platform features using Python, FastAPI, TypeScript, and LLM frameworks like LangGraph.
Develop and maintain backend systems and REST APIs for an Indonesian cybersecurity company, handling on-premise and cloud deployments, data management, and automation using Python, Docker, and cloud platforms.
We are looking for the right people — people who want to innovate, achieve, grow and lead. We attract and retain the best talent by investing in our employees and empowering them to develop themselves and their…
Leads a team to design and implement generative AI and data science solutions for enterprise clients, focusing on multi-agent systems, RAG, and MLOps using Python, Java, and cloud platforms.
Designs and implements generative AI and data science solutions for banking, insurance, and industrial clients, focusing on Python-based AI systems, MLOps, and cloud platforms.
Leads end-to-end delivery of enterprise AI/ML systems, including chatbots, agent-based workflows, and cloud-native platforms, using Python, cloud services, and MLOps practices.
Lead a team building enterprise AI/ML systems, from architecture to deployment, including chatbots, agent workflows, and cloud-native platforms using Python, cloud services, and MLOps tools.
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