Senior Software Engineer - Infrastructure

As a Senior Infrastructure Software Engineer, you will architect, build, and operate the core backend and deployment systems that power the Lexsi AI platform. You will own multi-cloud, serverless, and stateless AI deployments, ensuring our systems scale seamlessly across environments of any size while maintaining correctness, reliability, and cost efficiency. This role is ideal for someone who thinks like SDE + Platform Engineer + DevOps, and takes pride in owning systems end-to-end.

Responsibilities:

• Design and build Python-based backend services that power core platform functionality and AI workflows.
• Architect and operate AI/LLM inference and serving infrastructure at production scale.
• Build stateless, serverless, and horizontally scalable systems that can run across environments of varying sizes.
• Design multicloud infrastructure across AWS, Azure, and GCP with portability and reliability as first-class goals.
• Deploy and manage containerised workloads using Docker, Kubernetes, ECS, or equivalent systems.
• Build and operate distributed compute systems for AI workloads, including inference-heavy and RL-style execution patterns.
• Implement Infrastructure as Code using Terraform, CloudFormation, Pulumi, or similar tools.
• Own CI/CD pipelines for backend services, infrastructure, and AI workloads.
• Optimise GPU and compute usage for performance, cost, batching, and autoscaling.
• Define and enforce reliability standards targeting 99%+ uptime across critical services.
• Build observability systems for latency, throughput, failures, and resource utilisation.
• Implement security best practices across IAM, networking, secrets, and encryption.
• Support compliance requirements (SOC 2 ISO, HIPAA) through system design and evidence-ready infrastructure.
• Lead incident response, root cause analysis, and long-term reliability improvements.
• Collaborate closely with ML engineers, product, and leadership to translate AI requirements into infrastructure design.

Requirements:

• 3+ years of hands-on experience in backend engineering, platform engineering, DevOps, or infrastructure-focused SDE roles.
• Strong Python expertise with experience building and running production backend services.
• Experience with Python frameworks such as FastAPI, Django, Flask, or equivalent.
• Deep hands-on experience with Docker and Kubernetes in production environments.
• Practical experience designing and operating multi-cloud infrastructure.
• Strong understanding of Infrastructure as Code and declarative infrastructure workflows.
• Experience building and maintaining CI/CD pipelines for complex systems.
• Solid understanding of distributed systems, async processing, and cloud networking.
• Strong ownership mindset with the ability to build, run, debug, and improve systems end-to-end.

Nice to Have:

• Experience deploying AI or LLM workloads in production environments.
• Familiarity with model serving frameworks such as KServe, Kubeflow, Ray, etc.
• Experience running GPU workloads, inference batching, and rollout strategies.
• Exposure to serverless or hybrid serverless architectures for AI systems.
• Experience implementing SLO/SLA-driven reliability and monitoring strategies.
• Prior involvement in security audits or compliance-driven infrastructure work.
• Contributions to open-source infrastructure or platform projects.
• Strong system design documentation and architectural reasoning skills.