Sr Advanced Cloud Developer
Honeywell
Job Description
Job Description
Job Description
We are seeking a highly experienced Sr Advanced Cloud Developer with deep expertise in cloud-native engineering, large-scale distributed systems, modern data platforms, and applied AI/ML. This role blends advanced software engineering with cloud architecture, data engineering, and machine learning operations. You will design intelligent, scalable systems, lead complex initiatives, and elevate engineering excellence across the organization. Responsibilities KEY RESPONSIBILITIES Cloud Engineering & Architecture- Architect and build cloud-native applications and platforms on Azure, AWS, or GCP.
- Design serverless functions, and event-driven architectures.
- Implement Infrastructure-as-Code using Terraform, ARM/Bicep, or CloudFormation.
- Develop secure, automated CI/CD pipelines for continuous integration, deployment, and monitoring.
- Optimize cloud compute, storage, networking, and data processing for performance and cost efficiency.
- Enforce cloud security best practices, identity management, and compliance controls.
- Lead end-to-end development of mission-critical systems with a focus on performance, reliability, and maintainability.
- Write high-quality, testable code in Python, Java, Scala, Go, or C#.
- Conduct deep technical reviews and influence long-term architectural direction.
- Drive engineering best practices across teams, including code quality, observability, and performance optimization.
- Build, train, evaluate, and deploy machine learning models using frameworks like PyTorch, TensorFlow, and Scikit-learn.
- Design and maintain ML pipelines, including data ingestion, feature engineering, training, and model serving.
- Implement MLOps workflows using MLflow, Feature Store, Databricks Model Serving, or cloud-native ML platforms.
- Collaborate with data scientists to productionize models and ensure reliability, scalability, and observability.
- Build scalable ETL/ELT pipelines using Databricks, Apache Spark, Delta Lake, and Auto Loader.
- Optimize large-scale data processing jobs for performance and cost.
- Implement data quality, governance, and lineage frameworks.
- Manage Databricks clusters, jobs, workflows, and MLflow integrations.
- Partner with product, data science, cloud engineering, and platform teams to deliver end-to-end solutions.
- Communicate complex technical concepts clearly to both technical and non-technical audiences.
- Mentor engineers and contribute to a culture of innovation, learning, and engineering excellence.
- 8-12+ years of professional software or cloud engineering experience.
- Strong expertise in cloud-native development on Azure, AWS, or GCP.
- Deep experience with Databricks, Apache Spark, Delta Lake, and large-scale data processing.
- Hands-on experience deploying ML models in production environments.
- Proficiency in Python and at least one additional language (Java, Scala, Go, C#, or TypeScript).
- Strong understanding of distributed systems, microservices, and system design.
- Experience with modern CI/CD pipelines.
- Proven ability to deliver complex, high-impact systems at scale.
- Bachelor's degree or higher in Computer Science or related field
- Experience with LLMs, vector databases, and modern AI architectures.
- Expertise in serverless computing, event streaming (Kafka, Event Hubs), or real-time data processing.
- Familiarity with cloud-native ML platforms (Azure ML, SageMaker, Vertex AI).
- Strong background in cloud security, identity management, and compliance.
- Experience leading engineering teams or driving multi-team technical initiatives.
- Contributions to open-source or AI/ML communities.
- Experience designing scalable microservices, APIs
- Experience with Docker, Kubernetes
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Vacancy posted a month ago
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