We are helping an on-demand, autonomous ride-hailing company find a Software Engineer to design and build production-grade AI applications, agents, and conversational systems.
In this role, you’ll develop AI-powered products that support complex task execution, decision-making, and customer interactions. You’ll evaluate and integrate large language models, build Retrieval-Augmented Generation systems, and partner with cross-functional teams to deliver scalable, reliable AI solutions.
The ideal candidate is an experienced software engineer with a strong Python and machine learning background, hands-on experience building AI applications, and a practical understanding of how to balance model accuracy, latency, cost, and user experience.
As a Software Engineer, you’ll:
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Design and develop AI agents and autonomous systems capable of complex task execution and decision-making.
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Build conversational AI applications, including chatbots and voice-based customer service systems.
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Develop AI-powered integrations across applications, platforms, and services.
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Design and optimize Retrieval-Augmented Generation systems using vector databases, embeddings, retrieval strategies, and prompt engineering.
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Develop, implement, and optimize machine learning models using PyTorch.
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Evaluate and select large language models based on accuracy, latency, cost, capabilities, and user experience.
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Translate business requirements into scalable technical AI solutions in partnership with cross-functional teams.
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Architect, deploy, and maintain production-grade AI systems with a focus on reliability, scalability, security, and performance.
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Monitor AI system performance and improve model quality, response accuracy, and operational efficiency.
Requirements
Qualifications:
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6+ years Proficiency in Python for AI/ML development
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6+ years Experience with PyTorch (or willingness to learn for entry-level candidates)
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Understanding of AI agents and their application to real-world problems
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Hands-on experience or strong interest in building chatbots and/or voice-based conversational systems
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Knowledge of RAG system components: vector databases, embeddings, retrieval strategies, and prompt engineering
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Familiarity with major LLM providers (OpenAI, Anthropic, Google, Meta, etc.) and understanding of their trade-offs in terms of performance, cost, latency, and capabilities
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Understanding of transformer neural network architecture and attention mechanisms 6+ years
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Experience integrating AI capabilities into applications or eagerness to learn application development
Bonus Qualifications:
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Proficiency in Kotlin programming
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Full-stack development experience with both backend and frontend technologies
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Cloud software development experience, especially microservices architecture and integration
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Experience with REST APIs, gRPC, and/or Kafka for service communication and event-driven architectures
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Knowledge of cloud platforms (AWS, GCP, Azure) for AI deployment
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Familiarity with containerization and orchestration (Docker, Kubernetes)
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Experience with AI frameworks like LangChain, LlamaIndex, AutoGen, or similar tools Understanding of CI/CD pipelines and DevOps practices