Advanced AI Software Engineer

7 days ago

Gulbarga, Karnataka, India beBeeApplication Full time ₹ 20,00,000 - ₹ 25,00,000

AI Driven Application Developer

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We are seeking a skilled professional to design and develop AI driven applications utilizing Large Language Models (LLMs). This role involves architecting logic for AI Agents within our platform, enabling them to perform complex tasks in e-commerce and retail data orchestration pipelines.

Main Responsibilities:

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  • Design, develop, test, and maintain the core logic for AI Agents within FastAPI services. Orchestrate agent tasks, manage state, interact with platform data/workflows, and integrate LLM capabilities.
  • Integrate with external LLM provider APIs. Design, implement, and rigorously test effective prompts for diverse retail-specific tasks (generation, Q&A, summarization).
  • Implement and optimize Retrieval-Augmented Generation (RAG) patterns using vector databases to provide relevant context to LLM API calls made by agents.
  • Build and maintain the scalable FastAPI microservices that host AI Agent logic and handle interactions with LLMs and other platform components in a containerized environment (Docker, Kubernetes).
  • Prepare and preprocess data required for effective prompt context, RAG retrieval, and potentially for future fine-tuning tasks.
  • Collaborate with cross-functional teams to deliver AI features. Stay updated on LLM advancements and be prepared to learn and contribute to potential future in-house LLM fine-tuning and deployment efforts.

Requirements:

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  • 4–6 years of hands-on experience in software development with a strong focus on AI/ML application development.
  • Demonstrable experience integrating and utilizing external LLM APIs (e.g., OpenAI, Anthropic, Google) in applications.
  • Proven experience with Prompt Engineering techniques.
  • Strong Python programming skills.
  • Practical experience building and deploying RESTful APIs using FastAPI.
  • Experience designing and implementing application logic for AI-driven features or agents.
  • Understanding and practical experience with RAG concepts and vector databases (Pinecone, FAISS, etc.).
  • Solid understanding of core Machine Learning concepts and familiarity with frameworks like PyTorch, TensorFlow, or Hugging Face.
  • Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes) for application deployment.
  • Solid problem-solving skills and clear communication abilities.
  • Experience working effectively in an agile environment.
  • Willingness and capacity to learn and adapt towards future work involving deeper LLM customization and deployment.
  • Bachelor's or Master's degree in Computer Science, AI, or a related field.
  • Ability to work independently and collaborate effectively in a remote setting.

PREFERRED QUALIFICATIONS:

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  • Experience with frameworks like LangChain or LlamaIndex.
  • Experience with observability and debugging tools for LLM applications, such as LangSmith.
  • Experience with graph databases (e.g., Neo4j) and query languages (e.g., Cypher).
  • Experience with MLOps practices, applicable to both current application monitoring and future model lifecycle management.
  • Experience optimizing API call performance (latency/cost) or model inference.
  • Knowledge of AI security considerations and bias mitigation.

The successful candidate will have a solid foundation in AI/ML principles and experience with Large Language Models. They will be able to demonstrate their expertise through real-world examples and showcase their ability to adapt to new technologies and innovations in the field.

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