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<html><body>Location: Abu Dhabi Computer Science Fundamentals: Must demonstrate a deep understanding of Data Structures and Algorithms (e.g., time complexity, space complexity, and efficient data traversal). System Design &amp; SOLID Principles: Ability to apply architectural patterns (like Open/Closed principle) to ensure that the configurations created on our platform are extensible and maintainable. Database Mastery: Proficiency in both Relational (SQL) and NoSQL (MongoDB) databases. You must understand how to optimize queries for scale, manage primary/secondary keys, and implement indexing. API Ecosystems: Strong experience with RESTful APIs, WebSockets, and OAuth. You must be comfortable debugging integration issues between disparate enterprise systems. Python (Highly emphasized for AI/ML and data pipeline workflows).Java (The core backend language for many of their enterprise connectors).JavaScript / TypeScript (Used for frontend interactions and custom UI logic).Data Structures &amp; Algorithms (DSA): Candidates are expected to solve logic problems (e.g., finding elements in a list) without relying on built-in library functions like .sort(). Object-Oriented Design (SOLID): A deep understanding of the Open/Closed Principle is required to ensure that the configurations you build on the platform are maintainable. Database Knowledge: Proficiency in both SQL (Structured) and NoSQL (specifically MongoDB). You should be able to explain complex concepts like indexing, sharding, and "fail-safe" vs. "fail-fast" iteration. Experience: 4-6 years in building applications or AI Application or AI agents Good to have; Knowledge on Gen AI: LLMs, team of agents, MCP/A2A, RAG (chunking, embeddings, reranking, vector DBs), grounding/hallucination, AI governance, auditability, evaluation, HITL etc Model Ops: Prompt engineering, golden test set creation, agent-eval frameworks, A/B testing, regression analysis, basic fine tuning (PEFT/LoRA) Integrations: REST/GraphQL APIs, OAuth, webhooks; stitching systems into end-to-end flows. Product Thinking: Ability to unpack complex problems, map user journeys, and draft user stories &amp; acceptance criteria Basic Design Aptitude: Comfort with quick wireframes and basic visual flows Basic coding knowledge: Python, Java, C++, Groovy&nbsp;</body></html>

Location: Abu Dhabi Computer Science Fundamentals: Must demonstrate a deep understanding of Data Structures and Algorithms (e.g., time complexity, space complexity, and efficient data traversal). System Design &amp; SOLID Principles: Ability to apply architectural patterns (like Open/Closed principle) to ensure that the configurations created on our platform are extensible and maintainable. Database Mastery: Proficiency in both Relational (SQL) and NoSQL (MongoDB) databases. You must understand how to optimize queries for scale, manage primary/secondary keys, and implement indexing. API Ecosystems: Strong experience with RESTful APIs, WebSockets, and OAuth. You must be comfortable debugging integration issues between disparate enterprise systems. Python (Highly emphasized for AI/ML and data pipeline workflows).Java (The core backend language for many of their enterprise connectors).JavaScript / TypeScript (Used for frontend interactions and custom UI logic).Data Structures &amp; Algorithms (DSA): Candidates are expected to solve logic problems (e.g., finding elements in a list) without relying on built-in library functions like .sort(). Object-Oriented Design (SOLID): A deep understanding of the Open/Closed Principle is required to ensure that the configurations you build on the platform are maintainable. Database Knowledge: Proficiency in both SQL (Structured) and NoSQL (specifically MongoDB). You should be able to explain complex concepts like indexing, sharding, and "fail-safe" vs. "fail-fast" iteration. Experience: 4-6 years in building applications or AI Application or AI agents Good to have; Knowledge on Gen AI: LLMs, team of agents, MCP/A2A, RAG (chunking, embeddings, reranking, vector DBs), grounding/hallucination, AI governance, auditability, evaluation, HITL etc Model Ops: Prompt engineering, golden test set creation, agent-eval frameworks, A/B testing, regression analysis, basic fine tuning (PEFT/LoRA) Integrations: REST/GraphQL APIs, OAuth, webhooks; stitching systems into end-to-end flows. Product Thinking: Ability to unpack complex problems, map user journeys, and draft user stories &amp; acceptance criteria Basic Design Aptitude: Comfort with quick wireframes and basic visual flows Basic coding knowledge: Python, Java, C++, Groovy&nbsp;

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