Senior AI Application Developer Position

1 day ago

Ghaziabad, Uttar Pradesh, India beBeeDeveloper Full time ₹ 15,00,000 - ₹ 25,00,000
Job Title:

Artificial Intelligence Software Developer

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  • Key Responsibilities
  • Design, develop, test, and maintain the core logic for AI-driven applications using Python + FastAPI. Orchestrate task execution, manage state, interact with data/workflows, and integrate Large Language Model (LLM) capabilities.
  • Integrate with external LLM provider APIs. Design, implement, and rigorously test effective prompts for diverse 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 applications.
  • Build and maintain scalable microservices that host AI application logic and handle interactions with LLMs and other 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.
Required Skills & Qualifications:
  • 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 (important for understanding models and future adaptation).
  • 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:
  • 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.

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