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. • Exposure to Industrial Automation, IoT, Manufacturing Analytics, or Connected Products domains. • Understanding of AI evaluation, observability, guardrails, and governance frameworks. Experience with Semantic Search, Graph RAG, and Knowledge Graphs.