The Role
Designs and optimizes MLOps pipelines, LLM and agentic AI integrations, Databricks platforms, data lakes, and cloud infrastructure across GCP and Azure. Supports prompt engineering, model and API monitoring, CI/CD, containerization, data engineering, platform governance, and data lake operations. Collaborates with engineers, data scientists, and product managers to deliver AI solutions.
Summary Generated by Built In
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 Dynatrace or a similar observability platform for API monitoring
- Knowledge of LangSmith or a similar model monitoring platform
- 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
- Understanding of Docker and Kubernetes containerization
- Experience with data engineering, ETL, or big data technologies
- Good communication and problem-solving skills
- Experience 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
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The Company
