Team Description

At HPE Networking, the Digital Experience & Automation (DEA) team is reimagining how people experience support and services in a digital‐first world—setting new standards for the future of networking. We enable customers, partners, and employees through AI‐driven tools and modern platforms, transforming support into a unified, efficient, and simple experience that drives measurable value. Our mission is grounded in innovation with purpose: applying automation, AI, and data‐driven insights to simplify journeys, reduce friction, and create meaningful outcomes at every touchpoint.

DEA’s charter is to Client, evaluate, and scale solutions that embed intelligent technology into every interaction—delivering proactive and predictive experiences that shorten resolution times and accelerate task completion. We partner closely with technology providers, engineering, and business teams to deliver seamless omnichannel experiences and enable business transformation through data engineering, process optimization, and automation. Our work is fuelled by a passion for self‐service, intelligent automation, and building digital experiences that are intuitive, scalable, and human‐centric.

Responsibilities

- Demonstrate the ability to designs and implement the components of GenAI and/or Agentic AI solutions using state of the art technologies
- Understands architecture of large-scale software solutions that seamlessly merge traditional software modules with GenAI / AI components
- Efficiently uses software development life cycle (SDLC) principles across projects
- Knows implementation of Event-Driven Architectures (EDA)



- Proven ability to design decoupled systems using different messaging patterns (Sync / Async). Must be proficient with message brokers such as Amazon SQS, RabbitMQ, or Apache Kafka/MSK.
- Effectively leverages observability tools like New Relic, Grafana
- Demonstrates ability to break down complex problems into manageable, iterative technical solutions
- Knowledge on cloud technology (AWS preferred)
- Identify trends, patterns from dataset to scope opportunities for automation
- Aids deployment of machine learning models into production environments,
- Works with Front End, Data Engineering and DevOps teams to seamlessly integrate the software and deploy into production environment
- Develops, implements, and optimizes machine learning models and algorithms. This includes data pre-processing, feature engineering, model selection, hyperparameter tuning, and training on large datasets. Continuously monitor and improve model performance and accuracy.
- Demonstrates ability to design the experiments for given work and explain the experiments and their outcome to relevant stake holders
- Efficiently use Gen AI based coding tools (Copilot preferred) to implement, perform code review, develop test cases
- Exploration of new trends / developments in AI space (Example: Tensors, MCP, etc.)

Qualifications and Desired Experience:




- We are looking for a candidate with 4 to 8 years of experience in a Data science role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. Master’s degree is desirable
- Expertise in Python language stack and familiarity in Golang stack
- 1+ years of experience in development of production grade GenAI and/or AgenticAI solutions
- Candidates who have worked/working on Agentic AI shall be preferred
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and find opportunities for improvement.
- Strong analytic skills related to working with unstructured datasets.
- Experience working in technical support environment, working with dataset from CRM, H/W and S/W bugs data, machine logs
- Experience supporting and working with multi-functional teams in a multidimensional fast paced environment.
- Good team worker with excellent interpersonal, written, verbal and presentation skills
- Good knowledge on Software Development Life Cycle and Agile principles
- Familiar with one or more machine learning or statistical modeling tools such as Numpy, ScikitLearn, MLlib, Tensorflow, NLP libraries
- Experience working with Databricks, Snowflake platforms
- Experience with AWS cloud services: EC2, EMR, RDS, Redshift
- Valuable knowledge in – RESTful Services, implemented statelessness, Cache ability, and Uniform Interface across services
- Experience with AWS technologies
- Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
- Experience with data pipeline and workflow management tools

📌 Senior AI Engineer (Bengaluru)
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📍 Bengaluru