
Sr Advanced Software Engr
Honeywell · India · Hybrid
- Manufacturing & Industrial
- 10,001+ employees
- Charlotte, North Carolina
Mixed hiring record · median 50 days open
All reasons
- 45% of this employer's openings are over 60 days old
In its favour
- Still listed on the employer's own board
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.
Skills
- Machine Learning
- LLM
- Databricks
- GCP
- Azure
- Prompt Engineering
- Dynatrace
- MLflow
- Kubeflow
- Vertex AI
- Azure ML
- OpenAI
- Gemini
- Azure OpenAI
- Python
- GitHub Actions
- Azure DevOps
- Jenkins
- Docker
- Kubernetes
- ETL
- MLOps
- Generative AI
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