Full-Stack Development: Design, develop, and maintain both front-end and back-end components of our DELMIA Operation Planning & Optimization applications, ensuring seamless integration and optimal performance.
Front-End Expertise: Focus on user experience and interface design, utilizing technologies such as JavaScript, TypeScript, React, Leaflet, Redux, HTML, and CSS.
Back-End Proficiency: Leverage Java, Jakarta EE, Spring Framework, and Hibernate to build robust and scalable back-end systems.
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Impactful Work: Be part of a team that builds products and platforms used by thousands of global users. Your work will directly shape the future of our technology.
Global Collaboration: Join a diverse, international team spread across multiple countries. You'll work with talented professionals from different cultures and backgrounds, bringing fresh perspectives and global impact to every project.
Innovative Culture: We foster a culture of experimentation, learning, and continuous improvement. You’ll have the freedom to explore new ideas and technologies.
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This role is responsible for the design, development, testing, and deployment of Java-based applications, ensuring they meet business requirements and technical standards. The Senior Java Developer will play a key role in reviewing existing systems for improvements, delivering scalable backend solutions, and supporting the full software development lifecycle.
The role will also be expected to contribute to technical documentation, mentor team members, and participate in project planning and implementation.
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Act as a primary technical counterpart and architecture partner - designing, coding, and deploying a suite of custom, intelligent AI tools, and critically reviewing design decisions.
Enhance our system's ability to manage context windows, optimize token usage, and reduce attention noise when connecting LLMs to large codebase repositories.
Design and extend graph based code and document representations (e.g. property graphs, AST derived structures) and hybrid retrieval pipelines (dense + sparse + reranking/fusion) over vector databases.
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Lead and conduct in-depth technical due diligence on potential M&A targets, strategic partners, or new venture opportunities, assessing their R&D capabilities, technology stack, intellectual property (IP) portfolio, and product/process maturity.
Evaluate the technical feasibility, scalability, and integration challenges of external technologies or solutions. Identify technical risks and potential synergies between the company's existing R&D efforts and external opportunities.
Proactively monitor emerging technologies, scientific breakthroughs, and industry trends relevant to the company's strategic interests and R&D roadmap. Identify potential technology partners, startups, or research institutions for collaboration, investment, or acquisition.
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Agentic AI ArchitectureDesign and implement production-grade agentic systems using models such as Claude. Agent orchestration, tool calling, function calling, multi-agent architectures, planning and task decomposition, agent memory, context management, state machines and workflow engines, long-running agents, human-in-the-loop systems, autonomous execution, recovery and retry mechanisms, observability, and evaluation. You understand the difference between LLM → Agent → Workflow → Autonomous System, and when each is appropriate.
Agentic Loops & Self-OptimizationA major part of the role is building closed-loop systems: Goal → Plan → Execute → Observe → Evaluate → Learn → Re-plan → Execute. Systems that evaluate their own outputs, detect failed actions, identify root causes, adjust strategies, optimize prompts and tool selection, keep what works, roll back what does not, and improve over time. Reflection, critique, self-evaluation, feedback loops, reward signals, evaluation frameworks, automated experimentation, memory, retrieval, state management.
Claude / LLM EngineeringDeep practical experience with Claude/Anthropic APIs is highly desirable. Tool use, structured outputs, streaming, context management, prompt engineering, system prompts, long-context workflows, model routing, token optimization, latency and cost optimization, context compression, agent memory, LLM evaluation. Experience with other frontier models (OpenAI, Gemini, Llama or equivalent) is a plus.
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We are looking for an exceptional Senior/Staff Full Stack Engineer with 10+ years of engineering experience to build the next generation of AI-native software systems.
This is not a traditional full-stack role. We are looking for someone who understands how to build systems where AI agents can reason, execute, observe outcomes, learn from feedback, and continuously improve their own performance.
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We are looking for an exceptional Senior/Staff Full Stack Engineer with 10+ years of engineering experience to build the next generation of AI-native software systems.
This is not a traditional full-stack role. We are looking for someone who understands how to build systems where AI agents can reason, execute, observe outcomes, learn from feedback, and continuously improve their own performance.
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