Advanced Software Engr

Honeywell is seeking an experienced Advanced Software Engineer (Python AI/GenAI) to design, develop, and deploy enterprise-scale AI-powered applications. The ideal candidate should possess strong expertise in Python development, Machine Learning, Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and cloud-native architectures.

You will collaborate with product teams, architects, data scientists, and business stakeholders to build intelligent solutions that drive automation, productivity, and innovation across Honeywell products and platforms.

• Design, develop, and maintain scalable AI applications using Python.
• Build and deploy Generative AI solutions leveraging LLMs such as GPT, Llama, Claude, and Azure OpenAI.
• Develop RAG-based systems using vector databases and semantic search techniques.
• Create AI agents and multi-agent workflows using LangChain, LangGraph, CrewAI, or similar frameworks.
• Design and implement REST APIs and microservices.
• Integrate AI models with enterprise applications and cloud platforms.
• Collaborate with Data Science teams for model training, fine-tuning, evaluation, and deployment.
• Build CI/CD pipelines and automate model deployment workflows.
• Ensure AI solutions comply with security, governance, and responsible AI guidelines.
• Mentor junior engineers and participate in architecture reviews and technical leadership activities.
• Drive best practices for software engineering, code quality, testing, and observability.

• Bachelor's or Master's degree in Computer Science, Engineering, AI, Data Science, or related discipline.
• 6–9 years of software development experience.
• Strong programming expertise in Python.
• Hands-on experience with FastAPI, Flask, or Django.
• Experience with Machine Learning frameworks such as PyTorch or TensorFlow.
• Strong understanding of LLMs, Prompt Engineering, Fine-Tuning, Embeddings, and RAG architectures.
• Experience with LangChain, LlamaIndex, LangGraph, or equivalent AI frameworks.
• Knowledge of vector databases such as Pinecone, Milvus, FAISS, ChromaDB, or Weaviate.
• Experience with PostgreSQL, MySQL, MongoDB, or other databases.
• Familiarity with Docker, Kubernetes, Git, and CI/CD pipelines.
• Experience working on Azure, AWS, or GCP cloud platforms.
• Strong understanding of microservices architecture and API development.

Preferred Qualifications

• Experience with Azure OpenAI Services.
• Knowledge of MLOps tools such as MLflow, Kubeflow, SageMaker, or Azure ML.
• Experience with AI Agent frameworks and autonomous workflows.