Senior Backend Software Engineer

Senior Backend Software EngineerThis role has been designed as ‘’Onsite’ with an expectation that you will primarily work from an HPE office.

Who We Are:

Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.

Job Description:

Job Family Definition:

The AIOps team’s mission is to use advanced analytics, including AI/ML, to develop end-to-end solutions to automate (detect, remediate) networking workflows for our customers, and help extend AI/ML across the Juniper portfolio. We are looking for an experienced engineer to join our growing data science team of AI/ML and data-at-scale engineers.

Our ideal candidate brings their product development experience having developed performant inferencing implementations, practiced data science hygiene to develop ML models and is a team player. You will collaborate with product managers and domain specialists to develop solutions that are optimal and performant; And develop AIOps solutions that scale with terabytes of data.

Designs, develops and applies programs, methodologies and systems based on advanced analytic models (e.g. advanced statistics, operations research, computer science, process) to transform structured and unstructured data into meaningful and actionable information insights that drive decision making.

Management Level Definition:

Contributions have visible technical impact on a product or major subcomponent.  Applies in-depth professional knowledge and innovative ideas to solve complex problems. Visible contributions improve time-to-market, achieve cost reductions, or satisfy current and future unmet customer needs. Recognized internal authority on key technology area applying innovative principles and ideas. Provides technical leadership for significant project/program work. Leads or participates in cross-functional initiatives and contributes to mentorship and knowledge sharing across the organization.

What You’ll Do:

• Collaborate with product management and engineering teams to understand company needs, work with domain experts to identify relevant “signals” during feature engineering
• Take end-to-end ownership of designing, developing, and delivering scalable, high-performance backend services and distributed data processing solutions.
• Keep up to date with newest technology trends
• Communicate results and ideas to key decision makers
• Design and implement scalable data processing pipelines and backend data engineering solutions that support high-volume, distributed workloads.
• Optimize joint development efforts through appropriate database use and project design

What You Need to Bring:

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Mathematics, or a related technical field.
• 5+ years of software engineering experience with a strong focus on backend development.
• Strong programming skills in Python.
• Experience with PySpark/Spark for large-scale data processing.
• Hands-on experience with backend development using REST APIs, microservices, and distributed systems.
• Strong understanding of multithreading, concurrency, asynchronous programming, and performance optimization.
• Good understanding of software architecture and system design principles.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Experience with technologies such as Kafka, Flink, Elasticsearch, and Kubeflow is highly desirable.
• Familiarity with containerization and orchestration technologies such as Docker and Kubernetes is a plus.
• Strong problem-solving and analytical skills.

Preferred Qualifications

• Experience working with machine learning libraries such as Pandas, NumPy, Scikit-learn, MLlib, or TensorFlow.
• Knowledge of AI/ML and GenAI technologies and their production deployment.
• Experience building scalable ML platforms …