Sr Advanced Software Engr
Listed on Honeywell International’s official careers site. Posted October 26, 2026. Check that it is still open and apply there.
Apply on Honeywell International’s careers site →Job description
We are seeking a talented Senior Advanced Software Engineer to contribute to our machine learning operations (ML Ops), large language model (LLM) and agentic AI integration, Databricks administration, data lake management, and cloud platform projects. The ideal candidate will help design, implement, and optimize ML pipelines, support cloud infrastructure (GCP & Azure), participate in prompt engineering for generative and agentic AI, contribute to CI/CD practices, and assist with Databricks platform governance and data lake operations.
You will work closely with engineers, data scientists, and product managers to deliver innovative AI solutions.
Responsibilities
Required Qualifications
Bachelor’s degree in Computer Science, Engineering, or related field. 7+ years of software engineering experience, with 3+ years in ML Ops, agentic AI, Databricks, data lake, or cloud platforms. Knowledge of observability platform like Dynatrace for API monitoring, Lang smith for model monitoring. Experience with ML Ops tools (MLflow, Kubeflow, Vertex AI, Azure ML, etc.). Exposure to LLMs (OpenAI, Google Gemini, Azure OpenAI, etc.), agentic AI systems, and prompt engineering.
Familiarity with Databricks platform administration. Experience with data lake solutions (Azure Data Lake, GCP BigLake, etc.). Proficiency in Python; experience with other languages is a plus. Working knowledge of GCP and Azure cloud services. Experience with CI/CD pipelines (GitHub Actions, Azure DevOps, Jenkins, etc.). Understanding of containerization (Docker, Kubernetes). Experience with data engineering, ETL, or big data technologies.
Good communication and problem-solving skills.
Qualifications
Preferred Qualifications
Experience with working as senior DEVOPS/SRE or ML OPS engineer Familiarity with MLOps for LLMs, agentic AI, or generative AI. Contributions to open-source projects. Certifications in GCP, Azure, Databricks, Data Lake, or ML Ops.
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