AI/ML Senior Cloud Developer

Posted 2 Days Ago
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Bengaluru, Bengaluru Urban, Karnataka, IND
In-Office
Senior level
Artificial Intelligence • Cloud • Information Technology • Consulting
The Role
Designs and builds production-grade AI/ML and GenAI cloud solutions across the full ML lifecycle. Architects scalable GenAI, Agentic AI, RAG/GraphRAG, vector retrieval and knowledge-graph systems; leads MLOps/LLMOps, observability, governance, and cloud deployments; mentors engineers, drives platform standards, and integrates emerging AI technologies to ensure secure, reliable, and scalable AI services.
Summary Generated by Built In
AI/ML Senior Cloud Developer

  

This role has been designed as ‘Hybrid’ with an expectation that you will work on average 2 days per week 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:

   

What you’ll do:

Job Family Definition:

The AI/ML Expert Engineer designs and builds scalable, production-grade AI/ML solutions for mission-critical cloud applications. This role requires ownership of the complete machine learning lifecycle, including data analysis, feature engineering, model development, deployment, monitoring, and continuous improvement.

The engineer applies advanced technical expertise to architect, prototype, and implement AI/ML and GenAI-driven cloud solutions using modern MLOps practices for reliable, reproducible, and secure deployments.

Management Level Definition:

Applies advanced subject matter expertise to solve complex technical and business problems. Works independently on end-to-end AI/ML systems and contributes to architectural decisions. Provides technical leadership, mentors team members, and drives best practices across cross-functional teams.

Key Responsibilities

  • Responsible for design and development of complex products and platforms, AI/ML based cloud applications. Solution design, analysis, coding, testing, and integration for building efficient, scalable and robust systems.
  • Should know the AI/ML technologies and have hands-on experience with GenAI-based software development
  • Define enterprise AI/ML architecture and technical strategy.
  • Architect scalable GenAI, Agentic AI, RAG, and GraphRAG solutions.
  • Establish AI governance, observability, evaluation, and best practices.
  • Lead AI platform design, deployment standards, and operational excellence.
  • Mentor engineers and drive innovation across AI initiatives.
  • Evaluate and adopt emerging AI technologies and frameworks.
  • Reviews and evaluates designs, test plans, and develops code for compliance with cloud design and development guidelines and standards.
  • Deploys code and troubleshoots issues in application modules and the deployment environment.
  • Represents the engineering team in various technical forums and provides guidance and mentoring to less-experienced team members.
  • Drives innovation and integration of new technologies into projects and activities in the software systems design organization.

What you need to bring:

Required Skills

  • Strong programming skills in Python (Pandas, Scikit, NumPy ), Golang and Scripting.
  • Advanced ML, DL, NLP, and LLM expertise
  • Agentic AI, Multi-Agent Systems, RAG, GraphRAG
  • Vector Databases and Hybrid Retrieval Architectures
  • Knowledge Graph Databases (Dgraph, Neo4j, Neptune, etc.)
  • AI Evaluation and Observability (Langfuse, Ragas, OpenTelemetry, Arize Phoenix)
  • MLOps/LLMOps and AI Platform Engineering
  • Kubernetes, Distributed AI Systems, Cloud AI Platforms
  • AI Governance, Responsible AI, and Security
  • Strong architecture, leadership, and stakeholder management skills
  • AWS, Azure, or GCP

Education and Experience Required:

  • Bachelor's or master's degree in computer science, engineering, information systems, or closely related quantitative discipline.
  • Typically, 8-10 years’ hands-on experience in mentioned technologies,

Additional Skills:

Cloud Architectures, Cross Domain Knowledge, Design Thinking, Development Fundamentals, DevOps, Distributed Computing, Microservices Fluency, Full Stack Development, Release Management, Security-First Mindset, User Experience (UX)

What We Can Offer You:

Health & Wellbeing

We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.

Personal & Professional Development

We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division.

Unconditional Inclusion

We are unconditionally inclusive in the way we work and celebrate individual uniqueness. 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.

Let's Stay Connected:

Follow @HPECareers on Instagram to see the latest on people, culture and tech at HPE.

#india#networking

Job:

Engineering

Job Level:

TCP_04

    

    

HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity.

Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.

   

HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.

   

Recruitment Fraud Alert

We have become aware of an increase in fraudulent recruitment activities in which individuals impersonate our company or authorized recruitment agencies to offer fake employment opportunities. These scams may occur through false websites, emails, social media, or chat-based applications and often aim to obtain personal information or money. Please note that Hewlett Packard Enterprise (HPE), its direct and indirect subsidiaries and affiliated companies, and its authorized recruitment agencies/vendors will never charge a candidate a registration fee, hiring fee, or any other fee in connection with its recruitment and hiring process. We also never request personal information such as back account details, Social Security numbers, or national IDs via social media or chat applications.

All legitimate job opportunities will come through official company channels, and candidates are responsible for verifying the credentials of any third party claiming to represent the company. Any reliance on fraudulent communication is at the individual’s own risk, and HPE disclaims legal liability for any resulting damages. If you suspect recruitment fraud, do not share personal information or make any payments and report the incident to your local authorities immediately.

Skills Required

  • Strong programming skills in Python (Pandas, Scikit, NumPy), Golang and scripting
  • Advanced expertise in ML, DL, NLP, and LLMs
  • Experience with GenAI, Agentic AI, Multi-Agent Systems, RAG and GraphRAG
  • Experience with vector databases and hybrid retrieval architectures
  • Experience with knowledge graph databases (Dgraph, Neo4j, Amazon Neptune)
  • AI evaluation and observability tools (Langfuse, Ragas, OpenTelemetry, Arize Phoenix)
  • MLOps/LLMOps and AI platform engineering experience
  • Kubernetes, distributed AI systems, and cloud AI platform experience
  • Knowledge of AI governance, responsible AI practices, and security
  • Experience with AWS, Azure, or GCP
  • Bachelor's or Master's degree in computer science, engineering, information systems, or related quantitative discipline
  • Typically 8-10 years hands-on experience in the mentioned technologies
  • Cloud architectures, DevOps, distributed computing, microservices, full stack and release management
  • Strong architecture, leadership, and stakeholder management skills

Hewlett Packard Enterprise Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Hewlett Packard Enterprise and has not been reviewed or approved by Hewlett Packard Enterprise.

  • Parental & Family Support Policies include up to 26 weeks of fully paid parental leave with options for phased return to work, supplemented by backup care resources. Program materials emphasize broad availability, with specifics varying by country and role.
  • Wellbeing & Lifestyle Benefits Wellbeing initiatives such as Wellness Fridays and 60 hours of paid volunteer time provide additional paid time for rest, community, and flexibility. Hybrid/flexible work and wellbeing resources further reinforce a lifestyle-oriented package.
  • Retirement Support Offerings include a company 401(k) match, an Employee Stock Purchase Plan, and HSA seeding under certain medical plans. These financial benefits are positioned as solid components of the total rewards mix.

Hewlett Packard Enterprise Insights

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The Company
HQ: Houston, TX
85,422 Employees
Year Founded: 2015

What We Do

In 1939, Bill Hewlett and Dave Packard, college friends turned business partners, started the original Silicon Valley startup in the space of a rented Palo Alto garage. Starting with audio oscillators, the friends built the foundation for a company that would grow to become a global leader in enterprise technology. More than 75 years later, our success is exemplified through our employees’ drive to advance ideas that bring meaningful innovations to life for our customers and partners around the globe. We are guided by our mission to help customers use technology to turn ideas into value, and empower them to transform industries, markets and lives. We simplify Hybrid IT, power the Intelligent Edge and provide the expertise to make it all happen.

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