About this role
Honeywell Technologies is a global, pure-play automation company with a legacy of innovating to help solve the world’s most mission-critical challenges, enhancing the quality of life for people and communities around the world. We serve the building, industrial and process sectors with a broad portfolio of services, solutions and products, underpinned by our Honeywell Technologies Accelerator operating system and Honeywell Technologies Forge intelligence layer. By combining the deep domain expertise of our more than 50,000 employees with decades of data from our global installed base, we are uniquely positioned to lead the industrial sector’s transition from automation to autonomy.
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.
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.
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.