Job Description

Role Overview

We’re looking for an AI Software Engineer to join our team. You’ll play a key role in architecting and developing LLM-based AI solutions that drive innovation across our products. You thrive in a fast-paced environment, are passionate about cutting-edge AI technologies, and take initiative in exploring and implementing novel solutions. You’re proactive, self-driven, and excited about building AI- powered applications that impact users’ daily life.

Key Responsibilities

• Architect, develop, and deploy AI solutions such as GenAI.
• Design and implement systems for knowledge-intensive AI applications such as Retrieval-Augmented Generation (RAG).
• Explore, evaluate, and adopt emerging AI frameworks, tools, and technologies to maintain competitive advantage.
• Build and optimize vector database and graph database solutions for semantic search and knowledge representation.
• Integrate AI capabilities with cloud platforms such as Azure AI Foundry and AWS Bedrock.
• Collaborate with product teams to identify opportunities for AI-driven feature enhancement.
• Develop and maintain scalable, production-ready AI systems with robust monitoring and evaluation.
• Document technical approaches, share knowledge, and contribute to the AI engineering culture.

Job Requirements

•  Education
• Degree or Diploma in Computer Science, Software Engineering or a related field.

• Experience
• Minimum 3 years of software development experience with proficiency in Python and Node.js/JavaScript.
•  1+ years of hands-on experience building LLM-based AI applications.
• Demonstrable experience with RAG architectures, including document ingestion, chunking strategies, and retrieval optimization.
• Practical experience with vector databases (e.g., Pinecone, Weaviate, Milvus, or similar) or graph databases (e.g. Neo4j) for knowledge graph construction and querying.
• Fresh graduates are welcome to apply.

• Knowledge
• Strong understanding of LLM application fundamentals and Agentic AI / Workflow architectures.
• Proficiency with LLM frameworks such as LangChain, LlamaIndex, or similar orchestration tools.
• Experience with cloud AI services, particularly Azure AI Foundry and AWS Bedrock.
• Understanding of API design, microservices architecture, and distributed systems.
• Knowledge of version control (Git) and CI/CD practices.

• Key Competencies
• Fast Learner: Quickly grasp new concepts, frameworks, and technologies in the rapidly evolving AI landscape.
• Self-Learner: Proactively seek out new knowledge, experiment with emerging tools, and stay current with AI research and industry trends.
• Problem Solver: Analytical mindset with the ability to break down complex problems and develop effective solutions.
• Communication: Clear communicator who can articulate technical concepts to both technical and non-technical stakeholders.

• Tools Used
• Programming Languages: Python, Node.js/JavaScript
• Cloud AI Platforms: Azure AI Foundry, AWS Bedrock
• Vector Databases: Pinecone, Weaviate, Milvus, or similar
• Graph Databases: Neo4j
• AI Frameworks: LangChain, LlamaIndex, Hugging Face Transformers
• Development Tools: Git, Docker, CI/CD pipelines
• Additional: RESTful APIs, Microservices Architecture

• Nice to Have
• Experience with fine-tuning LLMs for domain-specific applications.
• Familiarity with LLMOps/MLOps practices and model deployment pipelines.
• Experience with prompt engineering and evaluation frameworks.

• What You Might Excel At
• AI Solution Architecture: Designing and implementing end-to-end AI systems that are scalable, maintainable, and production-ready.
• Technology Exploration: Identifying and evaluating emerging AI tools and frameworks to keep our stack at the cutting edge.
• Cross-Team Collaboration: Working seamlessly with engineering, product, and design teams to deliver AI-powered features that meet user needs.
• Continuous Innovation: Driving AI initiatives forward through self-directed learning, experimentation, and knowledge sharing.

Skills