ai infrastructure engineer

Deeplight

<div><p>DeepLight AI is a specialist AI and data consultancy with extensive experience implementing intelligent enterprise systems across multiple industries, with particular depth in financial services and banking. Our team combines deep expertise in data science, statistical modeling, AI/ML technologies, workflow automation, and systems integration with a practical understanding of complex business operations.</p><p>
The AI Platform Engineer helps design, build and maintain the on-premises AI Infrastructure for our client, a market leader in the environment sector. The engineer plays a key role in enabling large-scale machine learning and generative AI workloads by developing robust, scalable, and secure platform solutions that support data scientists and ML engineers across the organisation.</p><p>
The role requires deep <b>Kubernetes and infrastructure automation experience</b> to optimise performance, streamline deployments, and ensure reliability in an on-prem environment.</p><p><b>
Requirements</b></p><p></p><ul>
<li>
Design, deploy, and manage on-premises Kubernetes clusters for AI and ML workloads.</li>
<li>Develop and maintain infrastructure-as-code using tools like Terraform, Helm, or Ansible</li>
<li>Build and optimise AI/ML pipelines and MLOps workflows for model training, deployment, and monitoring.</li>
<li>Collaborate with data science and engineering teams to deliver high-performance computing environments for large model training and inference.</li>
<li>Implement resource management, observability, and scaling strategies for GPU-based workloads.</li>
<li>Manage containerisation, networking, and storage solutions for AI workloads.</li>
<li>Ensure security, compliance, and reliability of the AI platform.</li>
<li>Automate operational processes and continuously improve platform efficiency.</li>
</ul><p></p><p><b>
What we need from you:</b></p><p></p><ul>
<li>
Proven experience managing Kubernetes clusters on-premises (not just cloud-managed solutions).</li>
<li>Experience working in a Consultancy capacity.</li>
<li>Strong background in container orchestration, CI/CD, and automation.</li>
<li>Proficiency in Linux administration, Docker, and networking fundamentals.</li>
<li>Hands-on experience with infrastructure-as-code (Terraform, Helm, Ansible, etc.).</li>
<li>Experience supporting AI/ML workloads (e.g., TensorFlow, PyTorch, Hugging Face, Ray, Kubeflow).</li>
<li>Familiarity with GPU scheduling and resource management on Kubernetes.</li>
<li>Knowledge of monitoring and logging tools (Prometheus, Grafana, ELK, etc.).</li>
<li>Strong scripting skills (Python, Bash, or Go).</li>
<li>Understanding of DevOps and MLOps best practices.</li>
</ul><p><b>
Benefits</b></p><p><b>
Benefits &amp; Growth Opportunities:</b></p><ul><li>Competitive salary and performance bonuses</li><li>Comprehensive health insurance</li><li>Professional development and certification support</li><li>Opportunity to work on cutting-edge AI projects</li><li>International exposure and travel opportunities</li><li>Flexible working arrangements</li><li>Career advancement opportunities in a rapidly growing AI company</li></ul><p>
This position offers a unique opportunity to shape the future of AI implementation while working with a talented team of professionals at the forefront of technological innovation. The successful candidate will play a crucial role in driving our company's success in delivering transformative AI solutions to our clients.</p></div>

AI Platform Engineer

WAFER

<div><h2 class="jobSectionHeader"><b>About the role</b></h2><p>
Join our team as an intern to build the future of inference, GPU optimization and AI infrastructure. You'll work directly as a full-time engineer with the team to help define our technical direction and build the core systems that power our GPU optimization platform.</p><p></p><h2 class="jobSectionHeader"><b>
What You'll Do</b></h2><ul><li><p>
Build scalable infrastructure for AI model training and inference</p></li><li><p>
Lead technical decisions and architecture choices</p></li></ul><p></p><h2 class="jobSectionHeader"><b>
What We Look For</b></h2><p></p><h3 class="jobSectionHeader"><b>
Core Technical Expertise</b></h3><ul><li><p>
GPU Fundamentals: Deep understanding of GPU architectures, CUDA programming, and parallel computing patterns.</p></li><li><p>
Deep Learning Frameworks: Proficiency in PyTorch, TensorFlow, or JAX, particularly for GPU-accelerated workloads.</p></li><li><p>
LLM/AI Knowledge: Strong grounding in large language models (training, fine-tuning, prompting, evaluation).</p></li><li><p>
Systems Engineering: Proficiency in C++, Python, and possibly Rust/Go for building tooling around CUDA.</p></li></ul><h3 class="jobSectionHeader"><b>
Ideal Background</b></h3><ul><li><p>
Publications or open-source contributions in inference GPU computing or ML/AI for code are a plus.</p></li><li><p>
Hands-on experience with large-scale experiments, benchmarking, and performance tuning.</p></li></ul></div>

Member of Technical Staff (Spring Internship)

Member of Technical Staff (Winter Internship)

Google

<div>
 Google welcomes people with disabilities.
 <br/>
 <br/>
 Note: By applying to this position you will have an opportunity to share your preferred working location from the following:
 <strong>
  Paris, France; Dubai - United Arab Emirates; Tel Aviv, Israel
 </strong>
 .
 <strong>
  Minimum qualifications:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor's degree or equivalent practical experience.
  </li>
  <li>
   10 years of experience with cloud native architectures and modern cloud infrastructure (e.g., hardware shapes, sizes, auto-scaling, auto-provisioning, etc.).
  </li>
  <li>
   Experience with high performance infrastructure technology, on-premise infrastructure engineering, virtualization, or containerization platforms and orchestrators such as Slurm, Kubernetes, for building and operationalizing AI Models training and inference.
  </li>
  <li>
   Experience engaging with, and presenting to, technical stakeholders and executive leaders.
  </li>
  <li>
   Experience in networking, switching/routing for ethernet/RoCE/infiniband, in customer-facing or support roles.
   <br/>
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  </li>
 </ul>
 <strong>
  Preferred qualifications:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Master's degree in Computer Science, Mathematics, or a related technical field.
  </li>
  <li>
   Experience as an IT infrastructure consultant or enterprise architect working in data center investment strategies and proposals.
  </li>
  <li>
   Experience with AI Infrastructure systems, networking technologies (e.g., DPU, RoCE, InfiniBand), cooling, and accelerators, especially GPUs and TPUs.
  </li>
  <li>
   Experience on leveraging main AI hardware and software stacks and platforms to bring up and deploy large-scale AI compute clusters.
  </li>
  <li>
   Knowledge of the AI infrastructure market, including main technology providers, differentiators, and trends.
  </li>
  <li>
   Ability to grow rapidly in an environment, supported by a demonstrated entrepreneurial drive.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  About The Job
  <br/>
  <br/>
 </strong>
 When leading companies choose Google Cloud, it's a huge win for spreading the power of cloud computing globally. Once educational institutions, government agencies, and other businesses sign on to use Google Cloud products, you come in to facilitate making their work more productive, mobile, and collaborative. You listen and deliver what is most helpful for the customer. You assist fellow sales Googlers by problem-solving key technical issues for our customers. You liaise with the product marketing management and engineering teams to stay on top of industry trends and devise enhancements to Google Cloud products.
 <br/>
 <br/>
 As part of an entrepreneurial team in this rapidly growing business, you will play a key role in understanding the needs of our customers and help shape the future using AI technology. You will work with Google Cloud Platform (GCP's) technology and complete AI stack and position the same to our customers in all verticals.
 <br/>
 <br/>
 As a Customer Engineer, you will support Google Cloud sales teams to incubate, pilot, and deploy Google Cloud&rsquo;s industry leading AI/ML accelerators Tensor Processing Units/Graphical Processing Units (TPU/GPU) at AI innovators, large enterprises, and early stage AI startups. You will help customers innovate faster solutions using Google Cloud&rsquo;s flexible and open AI infrastructure.
 <br/>
 <br/>
 You will be working with Google customers on AI Infrastructure server and networking infrastructure deployments. In addition, you'll guide customer discussions on network topologies, compute/storage and support to bring up of server/network/cluster/cooling deployments. You will need to visit the customer data center during the bring up phase.
 <br/>
 <br/>
 Google Cloud accelerates every organization&rsquo;s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google&rsquo;s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
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  Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Understand and incorporate AI accelerators into overall cloud and IT strategy by designing large-scale training and inferencing platforms, using the latest and greatest accelerators Google Cloud has to offer.
  </li>
  <li>
   Demonstrate how Google Cloud is differentiated, highlighting the power of accelerators by working with customers on POCs, demonstrating features, optimizing model performance, profiling, and benchmarking.
  </li>
  <li>
   Work with customers to demonstrate and prototype Google Cloud technology integrations in customer/partner environments, including customer/partner data centers. Help the Account team to close agreements from a technical perspective.
  </li>
  <li>
   Influence Google Cloud strategy at the intersection of infrastructure and AI/ML by advocating for enterprise customer requirements, seamlessly collaborating with the AI Infra Dedicated Engineering team.
  </li>
  <li>
   Travel to customer sites, conferences, datacenters, and other related events as needed.
   <br/>
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   <br/>
  </li>
 </ul>
 Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .
</div>


Customer Engineer, Infrastructure Modernization, AI

Oracle

<div><p>OCI is Oracle&rsquo;s next-generation cloud platform, built for the most demanding enterprise workloads. We are focused on delivering high-performance computing, storage, networking, and platform services at global scale.
</p><p>The AI Platform, Services &amp; Solutions organization within OCI is building a robust ecosystem to support the end-to-end lifecycle of AI and machine learning workloads. From GPU infrastructure and training pipelines to model serving and deployment tools&mdash;we empower teams across Oracle and our customers to build and deploy AI at scale.
</p><p>We are looking for a Senior Software Engineer to join our growing team and help shape the future of AI infrastructure and services at Oracle. You will work on critical components of OCI&rsquo;s AI platform, including high-scale GPU cluster management, self-service ML infrastructure, and model serving systems.
</p><p>Work on critical AI infrastructure that powers Oracle&rsquo;s GenAI and ML initiatives. Contribute to high-impact projects with visibility across Oracle Cloud. Collaborate with top engineers and researchers in a fast-paced, innovation-driven environment. Grow your career in a supportive, mission-driven team building the future of enterprise AI.</p></div>
<br><div><div><div><div><div><div><div><p><b>What You&rsquo;ll Do
</b></p><ul><li>Build cloud service on top of the modern Infrastructure as a Service (IaaS) building blocks at OCI
</li><li>Design and build distributed, scalable, fault tolerant software systems
</li><li>Participate in the entire software lifecycle &ndash; development, testing, CI and production operations
</li><li>Leverage internal tooling at OCI to develop, build, deploy and troubleshoot software
</li><li>Participate in on-call for the service with the team
</li></ul><p><b>Qualifications
</b></p><ul><li>4+ years of experience shipping scalable, cloud native distributed systems
</li><li>Experience building control plane/data plane solutions for cloud native companies
</li><li>Proficient in Go, Java, Python
</li><li>Experienced at building highly available services, possessing knowledge of common service-oriented design patterns and service-to-service communication protocols
</li><li>Experience with production operations and best practices for putting quality code in production and troubleshoot issues when they arise
</li><li>Able to effectively communicate technical ideas verbally and in writing (technical proposals, design specs, architecture diagrams and presentations)
</li><li>BS in Computer Science, or equivalent experience
</li></ul><p><b>Preferred Qualifications
</b></p><ul><li>MS in Computer Science
</li><li>Experience with container orchestration like Kubernetes
</li><li>Experience in diagnosing, troubleshooting and resolving performance issues in complex environments
</li><li>Deep understanding of Unix-like operating systems
</li><li>Production experience with Cloud and ML technologies
</li><li>Generative AI, LLM, Machine learning experience</li></ul></div></div></div></div></div></div></div>

Software Developer

<div><div><div><div><div><div><div><div><div><div><div><div><div><p>Role Summary:
</p><p>As a Software Engineer (IC2), you will be responsible for developing AI powered services that scale our OCI AI Services. You will work with other senior engineers to implement scalable services/applications, automate deployment processes, and support operational excellence in production environments. This is a hands-on role suited for engineers eager to grow in distributed systems and AI infrastructure engineering that proactively manage cloud environments, enhance operational excellence, and deliver world-class customer experiences. If you&rsquo;re passionate about solving complex technical challenges and shaping the future of the autonomous cloud, this is your moment.
</p><p>Why Join Us
</p><ul><li>Gain hands-on experience with cutting-edge AI and cloud infrastructure
</li><li>Collaborate with experienced engineers and scientists across OCI
</li><li>Work in a supportive environment with strong opportunities for learning and career growth
</li><li>Help shape the foundations of Oracle&rsquo;s AI strategy and application of AI</li></ul></div></div></div></div></div></div></div></div></div></div></div></div></div><div></div>
<br><div><p>Qualifications
</p><p>General Skills
</p><ul><li>3+ years of experience delivering and operating large scale, highly available, distributed systems.
</li><li>Strong knowledge of Go or Java, and experience with scripting languages such as Python.
</li><li>Strong knowledge of data structures, algorithms, operating systems, and distributed systems fundamentals.
</li><li>Working familiarity with networking protocols (TCP/IP, HTTP) and standard network architectures.
</li><li>Strong troubleshooting skills and demonstrated ability to deliver quality code
</li><li>Experience working on multi-tenant, virtualized infrastructure a strong plus
</li><li>Excellent analytical skills and willingness to look at alternate paths to a solution
</li></ul><p>Specific Technology Exposure
</p><ul><li>A strong understanding of the architecture of the commonly available IaaS solutions and how they fit together. The candidate should have actively contributed in past for the design changes and architectural enhancements
</li><li>A strong understanding of the container technology like Docker and container orchestration technology like Kubernetes. Familiarity with managed Kubernetes service like Google Kubernetes Engine, Amazon Kubernetes Service will be an added advantage.
</li><li>Exposure to managing deployments on Azure, AWS and GCP is a big plus.
</li><li>Experience working with Open Source Communities is a big plus.
</li></ul><p>Additional Qualifications
</p><ul><li>Experience building AI scalable services/applications for enterprise
</li><li>Background in cloud operations, DevOps, or infrastructure monitoring domains
</li><li>Familiarity with Oracle Cloud Infrastructure or other major cloud platforms
</li><li>Exposure to AI/ML infrastructure, MCP, or LLM serving technologies
</li><li>Interest in distributed systems, observability, and scalability challenges
</li><li>Willingness to learn from senior engineers and contribute to high-impact projects</li></ul></div>

Member of Technical Staff

IMPACTO DIGIFIN TECHNOLOGIES PVT LTD

<div><div><b>Backend Engineer &acirc;&#128;&#147; Generative AI (Infra)</b></div><div>
<b>Experience Required:</b> 1.5 &acirc;&#128;&#147; 3 Years</div><div>
<b>Location:</b> Brookfield, Bangalore (In-office)</div><div>
<b>Employment Type:</b> Full-Time</div><h3 class="jobSectionHeader"><b>
About the Role</b></h3><div>
We are seeking a talented Backend Engineer with a focus on AI-driven systems, particularly in developing and maintaining scalable infrastructures for Generative AI applications. This role requires a solid background in backend engineering, API design, and AI model integration, with experience in LLMs, diffusion models, and multimodal AI systems.</div><div>
As a Backend Engineer, you will be responsible for building and managing backend systems that support AI services, ranging from model APIs to data retrieval pipelines, ensuring they are optimized for performance and security in production environments. Experience with enterprise-level systems, particularly in banking or financial services, is a significant advantage.</div><h3 class="jobSectionHeader"><b>
Key Responsibilities</b></h3><h4 class="jobSectionHeader"><b>
Backend Architecture &amp; Development</b></h4><div>
Design and develop scalable backend services to support AI and Generative AI workloads.</div><div>
Build and optimize RESTful and GraphQL APIs for model inference, prompt processing, and data access.</div><div>
Create modular backend components for high-performance, scalable AI operations.</div><h4 class="jobSectionHeader"><b>
Generative AI Pipeline Integration</b></h4><div>
Collaborate with AI engineers to integrate and deploy Generative AI models (LLMs, diffusion models, text-to-image, speech-to-text) in production.</div><div>
Implement retrieval-augmented generation (RAG) pipelines using vector databases like Pinecone, Weaviate, FAISS, or Milvus.</div><div>
Optimize AI model serving and inference with frameworks like TensorFlow Serving, TorchServe, FastAPI, or custom endpoints.</div><h4 class="jobSectionHeader"><b>
API Management &amp; Optimization</b></h4><div>
Develop secure APIs for AI-driven services, ensuring proper version control, authentication (OAuth2, JWT), and scalability.</div><div>
Integrate third-party AI APIs (OpenAI, Anthropic, Google Gemini, Stability AI) into internal systems.</div><div>
Monitor API usage, optimize for latency, and ensure high-throughput AI operations.</div><h4 class="jobSectionHeader"><b>
System &amp; Environment Setup</b></h4><div>
Set up backend environments using Docker, Kubernetes, and CI/CD pipelines for automated deployments.</div><div>
Manage scalable cloud environments (AWS, Azure, GCP) with load balancing and fault tolerance.</div><div>
Support development environments and backend utilities for cross-functional AI teams.</div><h4 class="jobSectionHeader"><b>
Performance &amp; Security</b></h4><div>
Optimize server performance for AI workloads through caching, queuing, and load balancing techniques.</div><div>
Ensure compliance with data privacy and security regulations, especially in financial domains.</div><div>
Implement observability tools like Prometheus, Grafana, and ELK Stack for performance monitoring.</div><h4 class="jobSectionHeader"><b>
Collaboration</b></h4><div>
Collaborate with AI/ML engineers, data scientists, frontend developers, and DevOps teams.</div><div>
Contribute to architecture discussions, backend documentation, and process improvements.</div><div>
Participate in agile ceremonies, code reviews, and design sessions.</div><h3 class="jobSectionHeader"><b>
Required Technical Skills</b></h3><div><b>
Languages:</b> Python (primary), Node.js, Java</div><div><b>
Backend Frameworks:</b> FastAPI, Flask, Django, Express.js, Spring Boot</div><div><b>
AI &amp; Generative Tools:</b></div><div>
Familiarity with LLMs (e.g., GPT, Claude, Gemini, LLaMA, Mistral)</div><div>
Experience with diffusion models (e.g., Stable Diffusion, Midjourney APIs)</div><div>
Knowledge of transformer models via Hugging Face or OpenAI APIs</div><div>
Understanding of prompt engineering and model-serving best practices</div><div><b>
Databases:</b> PostgreSQL, MongoDB, Redis, Elasticsearch</div><div><b>
Vector Databases:</b> Pinecone, Weaviate, Milvus, FAISS (for RAG systems)</div><div><b>
Infrastructure &amp; DevOps:</b> Docker, Kubernetes, Jenkins, GitLab CI/CD, AWS Lambda, ECS, or GCP Cloud Run</div><div><b>
Monitoring:</b> Prometheus, Grafana, ELK Stack, New Relic</div><div><b>
API Technologies:</b> REST, GraphQL, gRPC</div><h3 class="jobSectionHeader"><b>
Preferred Qualifications</b></h3><div>
Experience with AI product backend systems or enterprise software, especially in banking.</div><div>
Familiarity with AI pipeline orchestration tools (LangChain, LlamaIndex, Haystack).</div><div>
Understanding of model lifecycle management, vector embeddings, and inference scaling.</div><div>
Familiarity with data encryption, tokenization, and compliance standards (PCI DSS, ISO 27001).</div><h3 class="jobSectionHeader"><b>
Soft Skills</b></h3><div>
Strong problem-solving and debugging abilities.</div><div>
Excellent communication skills for collaborating with cross-functional teams.</div><div>
High attention to detail and performance optimization.</div><div>
Curiosity and enthusiasm for emerging AI technologies and backend architecture.</div><h3 class="jobSectionHeader"><b>
Education</b></h3><div>
Bachelor's or Master's degree in Computer Science, IT, AI, or a related field.</div><div>
Certifications in AI/ML, Cloud Architecture, or Backend Development are a plus.</div><h3 class="jobSectionHeader"><b>
Why Join Us</b></h3><div>
Work at the forefront of backend engineering and Generative AI innovation.</div><div>
Build production-ready systems for large-scale, intelligent applications.</div><div>
Collaborate with a team pushing the boundaries of AI applications and infrastructure optimization.</div><h3 class="jobSectionHeader"><b>
Work Schedule</b></h3><div><b>
Working Days:</b> Monday to Saturday (Alternate Saturdays leave)</div><div><b>
Timings:</b> 9:00 AM to 6:00 PM</div></div><div></div>

Backend Engineer – Generative AI (Infra) 2 to 4 years exp

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