Senior Software Engineer (python) – Gen AI

Adobe Adobe · Enterprise · Noida, India

Senior Software Engineer with Python and Generative AI expertise to lead the architecture and deployment of production-grade AI systems, focusing on LLMs, RAG, and Agentic workflows. Responsibilities include building scalable backend systems, implementing GenAI workflows, fine-tuning LLMs, developing APIs, managing data and MLOps, and providing technical leadership.

What you'd actually do

  1. Lead the build of scalable backend systems and robust architectures for platforms powered by artificial intelligence, ensuring high availability and security.
  2. Build and deploy production-scale Agentic AI workflows and multi-model RAG pipelines using frameworks like LangChain or LlamaIndex.
  3. Fine-tune LLMs using techniques like LoRA or QLoRA and perform prompt engineering to improve model accuracy and efficiency.
  4. Develop high-performance RESTful or GraphQL APIs (typically using FastAPI or Flask) to integrate AI models with enterprise applications.
  5. Implement data ingestion and preprocessing mechanisms, while overseeing LLMOps practices such as model versioning, monitoring, and CI/CD for AI services.

Skills

Required

  • Python
  • Generative AI
  • Large Language Models (LLMs)
  • Retrieval-Augmented Generation (RAG)
  • Agentic workflows
  • LangChain
  • LlamaIndex
  • LoRA
  • QLoRA
  • Prompt engineering
  • RESTful APIs
  • GraphQL APIs
  • FastAPI
  • Flask
  • Data ingestion
  • Data preprocessing
  • Model versioning
  • Model monitoring
  • CI/CD for AI services
  • Asynchronous programming (asyncio)
  • OOP
  • Design patterns
  • Hugging Face
  • PyTorch
  • TensorFlow
  • LangGraph
  • CrewAI
  • Vector databases
  • Pinecone
  • Weaviate
  • FAISS
  • AWS
  • Azure
  • GCP
  • Pandas
  • NumPy
  • SQL
  • NoSQL databases
  • Docker
  • Kubernetes
  • Jenkins
  • GitHub Actions

Nice to have

  • 7+ years in software development
  • 1-2 years specifically focused on Generative AI or LLM integration
  • Bachelor's degree or higher-level degree or equivalent experience in Computer Science, Engineering, or a related STEM field

What the JD emphasized

  • production-grade AI systems
  • production-scale Agentic AI workflows
  • LLMOps practices

Other signals

  • Deploying production-grade AI systems
  • Building and deploying production-scale Agentic AI workflows
  • Fine-tune LLMs
  • Implement data ingestion and preprocessing mechanisms
  • Overseeing LLMOps practices