Job Title: Forward Deployed Engineer – Cloud & AI Infrastructure Company: Host360

Location:
Onsite (Mumbai
- Andheri East) Employment Type: Full Time

Experience:
2–4 Years Function: Platform Engineering | AI Infrastructure Focus: Cloud Infrastructure | AI Platform Deployment | Software Engineering | Customer Engineering CTC – As per Industry Standards About Host360 At Host360, we are building a next-generation cloud and AI infrastructure platform that enables enterprises to modernize their infrastructure, deploy AI workloads, and run mission-critical applications at scale. Our offerings span public cloud, private cloud, GPU infrastructure, AI platforms, Kubernetes, bare-metal infrastructure, and managed cloud services. We help organizations build secure, scalable, and high-performance environments for modern applications and AI-driven workloads. We are looking for a Forward Deployed Engineer (FDE) who thrives at the intersection of software engineering, cloud infrastructure, and AI. You will work directly with customers to understand complex technical challenges, design and implement solutions, and take them from initial discovery to reliable production deployments. This is a hands-on engineering role for someone who enjoys solving real-world problems, building systems that work in production, and turning customer requirements into reusable engineering solutions. The Role As a Forward Deployed Engineer at Host360, you will work closely with customer engineering teams to deploy AI workloads, modernize infrastructure, and build production-ready cloud-native solutions. You will operate across software, infrastructure, and AI platforms, combining deep technical execution with customer collaboration. You will be expected to move beyond architecture discussions and prototypes to build, deploy, troubleshoot, and optimize working systems in real enterprise environments. You will own outcomes such as deployment speed, system reliability, performance, resource utilization, and customer adoption. This role is ideal for engineers who enjoy working across multiple layers of the technology stack and can independently take a problem from ambiguity to a working production solution. What You’ll Do 1. Customer Engineering & Solution Development
• Work directly with customer engineering and platform teams to understand technical requirements, infrastructure challenges, and business objectives.
• Translate ambiguous problems into clear technical solutions, implementation plans, and measurable success criteria.
• Lead technical discovery sessions, architecture discussions, proof-of-concepts, and hands-on implementation workshops.
• Build and deploy solutions within customer environments, adapting to their existing infrastructure, applications, and operational constraints.
• Troubleshoot complex technical issues and take ownership until the solution is stable and operational. 2. Cloud & Infrastructure Engineering
• Design, deploy, and optimize cloud infrastructure across public cloud, private cloud, hybrid cloud, and bare-metal environments.
• Implement infrastructure solutions involving compute, storage, networking, security, and virtualization.
• Work with containerized applications, Docker, Kubernetes, and cloud-native platforms.
• Build and maintain infrastructure automation using Python, Bash, Terraform, Ansible, or similar tools.
• Support application migration, infrastructure modernization, workload optimization, and platform integration.
• Diagnose infrastructure bottlenecks involving networking,



storage, compute, resource allocation, and application performance. 3. AI Infrastructure & Platform Deployment
• Help customers deploy and operationalize AI and Generative AI workloads on cloud and GPU infrastructure.
• Set up environments for LLM inference, model serving, AI applications, and agent-based workflows.
• Work with GPU-enabled infrastructure, containerized AI workloads, model runtimes, and inference-serving frameworks.
• Integrate AI applications with APIs, databases, storage systems, and enterprise platforms.
• Assist in building reliable AI deployment pipelines with appropriate monitoring, resource management, and scaling mechanisms.
• Troubleshoot AI workload issues involving GPU utilization, memory consumption, latency, throughput, model serving, and infrastructure performance. 4. Software Engineering & Automation
• Build production-grade tools, scripts, APIs, integrations, and automation workflows that solve customer engineering problems.
• Use Python and, where appropriate, Go, TypeScript, or JavaScript to develop practical engineering solutions.
• Develop integrations across cloud platforms, infrastructure management systems, observability tools, and AI services.
• Automate repetitive operational tasks, deployment workflows, infrastructure provisioning, and troubleshooting processes.
• Use AI-assisted development tools such as Cursor, Claude Code, Codex, or similar tools to accelerate engineering workflows.
• Build reusable components, deployment templates, and automation frameworks that can be applied across multiple customer environments. 5. Production Reliability & Optimization
• Take ownership of deployed solutions beyond the initial implementation, including troubleshooting, performance tuning, and continuous improvement.
• Implement monitoring, logging, metrics, tracing, and alerting to maintain production reliability.
• Investigate incidents, identify root causes, and implement corrective and preventive measures.
• Evaluate performance, scalability, security, resource utilization, and cost efficiency.
• Establish safe deployment practices, rollback mechanisms, and operational runbooks.
• Measure the impact of deployed solutions through meaningful technical and business outcomes. 6. Product Feedback & Reusable Engineering
• Collaborate with Host360’s Platform Engineering, Product, and AI Infrastructure teams to address challenges encountered during customer deployments.
• Convert recurring customer requirements into reusable tools, platform capabilities, and product improvements.
• Document architecture decisions, deployment procedures, troubleshooting guides, and implementation patterns.
• Develop reusable reference architectures, automation scripts, and technical playbooks.
• Share real-world feedback to improve Host360’s cloud platform, AI infrastructure, and developer experience. Required Skills & Experience
• Strong engineering mindset with the ability to independently investigate problems, design solutions, write code, and deliver working systems.




• 2-4 years of hands-on experience in software engineering, cloud infrastructure, platform engineering, DevOps, or a closely related technical role.
• Strong programming experience in Python, Go, TypeScript, JavaScript, or another relevant language, with the ability to build practical engineering tools and integrations.
• Hands-on experience designing, deploying, or operating cloud infrastructure across AWS, Azure, GCP, private cloud, or hybrid cloud environments.
• Experience working with Linux systems, networking fundamentals, APIs, distributed systems, and production troubleshooting.
• Practical experience with Docker, Kubernetes, containerized applications, or cloud-native deployment environments.
• Experience with infrastructure automation, CI/CD pipelines, configuration management, or Infrastructure as Code.
• Ability to understand customer requirements and translate them into technical architectures and working implementations.
• Strong debugging and problem-solving skills across application, infrastructure, and platform layers.
• Ability to take ownership of a problem from discovery and implementation through deployment, troubleshooting, and optimization.
• Robust communication skills and the ability to work directly with customer engineers and technical stakeholders. Preferred Qualifications
• Experience deploying or supporting AI, Generative AI, LLM, or machine learning workloads in production.
• Familiarity with GPU infrastructure, NVIDIA GPUs, CUDA fundamentals, GPU scheduling, or GPU resource utilization.
• Experience with model serving and inference frameworks such as vLLM, NVIDIA Triton Inference Server, or similar technologies.
• Familiarity with open-source AI models, model runtimes, inference optimization, and AI application frameworks.
• Experience with Terraform, Ansible, Helm, GitOps, or Kubernetes operators.
• Exposure to private cloud and virtualization technologies such as OpenStack, VMware, Nutanix, or Proxmox.
• Experience with observability platforms, Prometheus, Grafana, OpenTelemetry, or distributed tracing.
• Familiarity with databases, object storage, data pipelines, and enterprise application integration.
• Experience using AI coding assistants to build, debug, test, and maintain production software.
• Previous experience in customer engineering, solutions engineering, technical consulting, or embedded engineering roles. What We’re Looking For We value demonstrated engineering ability, practical problem-solving, and ownership over a particular combination of degrees, certifications, or technology keywords. You may be a strong fit if you:
• Enjoy getting hands-on with unfamiliar systems and figuring out how they work.
• Can move from an unclear customer problem to a working implementation without relying entirely on predefined instructions.
• Are comfortable switching between application code, cloud infrastructure, networking, containers, and AI workloads.
• Prefer building and debugging real systems over producing architecture documents alone.
• Can explain technical trade-offs clearly to engineers and non-technical stakeholders.
• Take responsibility for production outcomes rather than considering a deployment complete when the initial setup is finished.
• Enjoy learning new technologies and sharing what you learn with the wider engineering team. At Host360, we are looking for engineers who don’t just recommend solutions — they build them, deploy them, and make them work in production.

📌 Forward Deployed Engineer – Cloud (Mumbai)
🏢 Host360
📍 Mumbai