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.
ResponsibilitiesRequired 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.
Skills Required
- Bachelor's degree in Computer Science, Engineering, or a related field
- 7+ years of software engineering experience
- 3+ years of experience in MLOps, agentic AI, Databricks, data lakes, or cloud platforms
- Knowledge of observability and model monitoring platforms such as Dynatrace and LangSmith
- Experience with MLOps tools such as MLflow, Kubeflow, Vertex AI, or Azure ML
- Exposure to LLMs, agentic AI systems, and prompt engineering
- Familiarity with Databricks platform administration
- Experience with data lake solutions such as Azure Data Lake or GCP BigLake
- Proficiency in Python
- Working knowledge of GCP and Azure cloud services
- Experience with CI/CD pipelines such as GitHub Actions, Azure DevOps, or Jenkins
- Understanding of Docker and Kubernetes containerization
- Experience with data engineering, ETL, or big data technologies
- Good communication and problem-solving skills
- Experience working as a senior DevOps, SRE, or MLOps engineer
- Familiarity with MLOps for LLMs, agentic AI, or generative AI
- Contributions to open-source projects
- Certifications in GCP, Azure, Databricks, data lakes, or MLOps
Honeywell Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Honeywell and has not been reviewed or approved by Honeywell.
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Retirement Support — Retirement benefits are anchored by a strong 401(k) match with clear vesting and annual funding mechanics. Plan administration and education resources further reinforce long‑term savings support.
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Leave & Time Off Breadth — Time away provisions include company holidays, flexible vacation for many exempt roles, and paid sick time. These policies contribute meaningful breadth beyond base pay.
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Parental & Family Support — Paid parental leave is available to all parents with flexible usage options, and certain family‑building supports are included. Birth mothers can coordinate leave with short‑term disability for extended coverage.
Honeywell Insights
What We Do
Honeywell is a Fortune 500 company that invents and manufactures technologies to address tough challenges linked to global macrotrends such as safety, security, and energy. With approximately 110,000 employees worldwide, including more than 19,000 engineers and scientists, we have an unrelenting focus on quality, delivery, value, and technology in everything we make and do.
