Senior Software Engineer - Infrastructure

Lexsi Labs; Mumbai; On-site; INR 4,000,000 - 7,500,000; Full time

Job summary

LexsiLabs is seeking a Senior Infrastructure Software Engineer to architect, build, and operate the core backend and deployment systems powering the LexsiAI platform. You will own multi-cloud, serverless, and stateless AI deployments to ensure correctness, reliability, and cost efficiency at scale.

The role is ideal for someone who thinks like an SDE+Platform Engineer+DevOps, taking pride in end-to-end ownership of systems and outcomes, across production environments and enterprise workloads.

Qualifications

• 3+ years 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.

Responsibilities

• Design and build Python-based backend services powering 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 across environments of varying size.
• Design multi-cloud infrastructure across AWS, Azure, and GCP with portability and reliability as goals.
• Deploy and manage containerized workloads using Docker, Kubernetes, ECS, or equivalents.
• Build and operate distributed compute systems for AI workloads, including inference-heavy and RL-style patterns.
• Implement Infrastructure as Code using Terraform, CloudFormation, Pulumi, or similar tools.
• Own CI/CD pipelines for backend services, infrastructure, and AI workloads.
• Optimize GPU and compute usage for performance, cost, batching, and auto-scaling.
• Define and enforce reliability standards targeting 99%+ uptime across critical services.
• Build observability for latency, throughput, failures, and resource utilization.
• Implement security best practices across IAM, networking, secrets, and encryption.
• Support compliance requirements (SOC2, ISO, HIPAA) through design and evidence-ready infrastructure.
• Lead incident response, root-cause analysis, and long-term reliability improvements.
• Collaborate with ML engineers, product, and leadership to translate AI requirements into infrastructure design.

Skills

Python

Backend engineering

DevOps

SRE mindset

Tools

Docker

Kubernetes

FastAPI

Django

Flask

Terraform

CloudFormation

Pulumi

Job description

LexsiLabsisoneoftheleadingfrontierlabsfocusedonbuildingaligned,interpretable,andsafeSuperintelligence.Ourworkspansefficientalignmentmethods,interpretability-ledsystemdesign,andscalableAIplatformsthatoperatereliablyacrossenterpriseandregulatedenvironments.OurmissionistobuildAIsystemsthatarepowerful,transparent,andproduction-gradebydesign.

Ourteamoperateswithdeeptechnicalownership,minimalhierarchy,andastrongbiastowardbuildingsystemsthatworkatscale.AtLexsi.ai,infrastructureisnotsupportwork.Itisacoreproductcapability.

Asa SeniorInfrastructureSoftwareEngineer ,youwillarchitect,build,andoperatethecorebackendanddeploymentsystemsthatpowertheLexsiAIplatform.Youwillownmulti-cloud,serverless,andstatelessAIdeployments,ensuringoursystemsscaleseamlesslyacrossenvironmentsofanysizewhilemaintainingcorrectness,reliability,andcostefficiency.

Thisroleisidealforsomeonewhothinkslike SDE+PlatformEngineer+DevOps ,andtakesprideinowningsystemsend-to-end.

LexsiLabsisoneoftheleadingfrontierlabsfocusedonbuildingaligned,interpretable,andsafeSuperintelligence.Ourworkspansefficientalignmentmethods,interpretability-ledsystemdesign,andscalableAIplatformsthatoperatereliablyacrossenterpriseandregulatedenvironments.OurmissionistobuildAIsystemsthatarepowerful,transparent,andproduction-gradebydesign.

Ourteamoperateswithdeeptechnicalownership,minimalhierarchy,andastrongbiastowardbuildingsystemsthatworkatscale.AtLexsi.ai,infrastructureisnotsupportwork.Itisacoreproductcapability.

Asa SeniorInfrastructureSoftwareEngineer ,youwillarchitect,build,andoperatethecorebackendanddeploymentsystemsthatpowertheLexsiAIplatform.Youwillownmulti-cloud,serverless,andstatelessAIdeployments,ensuringoursystemsscaleseamlesslyacrossenvironmentsofanysizewhilemaintainingcorrectness,reliability,andcostefficiency.

Thisroleisidealforsomeonewhothinkslike SDE+PlatformEngineer+DevOps ,andtakesprideinowningsystemsend-to-end.

Responsibilities

• DesignandbuildPython-basedbackendservicesthatpowercoreplatformfunctionalityandAIworkflows.
• ArchitectandoperateAI/LLMinferenceandservinginfrastructureatproductionscale.
• Buildstateless,serverless,andhorizontallyscalablesystemsthatcanrunacrossenvironmentsofvaryingsizes.
• Designmulti-cloudinfrastructureacrossAWS,Azure,andGCPwithportabilityandreliabilityasfirst-classgoals.
• DeployandmanagecontainerizedworkloadsusingDocker,Kubernetes,ECS,orequivalentsystems.
• BuildandoperatedistributedcomputesystemsforAIworkloads,includinginference-heavyandRL-styleexecutionpatterns.
• ImplementInfrastructureasCodeusingTerraform,CloudFormation,Pulumi,orsimilartools.
• OwnCI/CDpipelinesforbackendservices,infrastructure,andAIworkloads.
• OptimizeGPUandcomputeusageforperformance,cost,batching,andautoscaling.
• Defineandenforcereliabilitystandardstargeting99%+uptimeacrosscriticalservices.
• Buildobservabilitysystemsforlatency,throughput,failures,andresourceutilization.
• ImplementsecuritybestpracticesacrossIAM,networking,secrets,andencryption.
• Supportcompliancerequirements(SOC2,ISO,HIPAA)throughsystemdesignandevidence-readyinfrastructure.
• Leadincidentresponse,rootcauseanalysis,andlong-termreliabilityimprovements.
• CollaboratecloselywithMLengineers,product,andleadershiptotranslateAIrequirementsintoinfrastructuredesign.

RequiredQualifications

• 3+yearsofhands-onexperienceinbackendengineering,platformengineering,DevOps,orinfrastructure-focusedSDEroles.
• StrongPythonexpertisewithexperiencebuildingandrunningproductionbackendservices.
• ExperiencewithPythonframeworkssuchasFastAPI,Django,Flask,orequivalent.
• Deephands-onexperiencewithDockerandKubernetesinproductionenvironments.
• Practicalexperiencedesigningandoperatingmulti-cloudinfrastructure.
• StrongunderstandingofInfrastructureasCodeanddeclarativeinfrastructureworkflows.
• ExperiencebuildingandmaintainingCI/CDpipelinesforcomplexsystems.
• Solidunderstandingofdistributedsystems,asyncprocessing,andcloudnetworking.
• Strongownershipmindsetwiththeabilitytobuild,run,debug,andimprovesystemsend-to-end.

NicetoHave

• ExperiencedeployingAIorLLMworkloadsinproductionenvironments.
• FamiliaritywithmodelservingframeworkssuchasKServe,Kubeflow,Rayetc.
• ExperiencerunningGPUworkloads,inferencebatching,androlloutstrategies.
• ExposuretoserverlessorhybridserverlessarchitecturesforAIsystems.
• ExperienceimplementingSLO/SLA-drivenreliabilityandmonitoringstrategies.
• Priorinvolvementinsecurityauditsorcompliance-driveninfrastructurework.
• Contributionstoopen-sourceinfrastructureorplatformprojects.
• Strongsystemdesigndocumentationandarchitecturalreasoningskills.

WhatSuccessLooksLike

• Lexsi'sAIplatformscalescleanlyacrosscloudprovidersanddeploymentsizes.
• Inferencesystemsarereliable,observable,andcost-efficientunderrealload.
• Engineeringteamsshipfasterbecauseinfrastructureispredictableandwell-designed.
• Incidentsarerare,understooddeeplywhentheyoccur,andleadtodurablefixes.
• Infrastructuredecisionssupportlong-termplatformscalability,notshort-termhacks.

NextSteps&InterviewProcess

• Take-homeassignmentfocusedonrealinfrastructureandscalingproblems.
• Deeptechnicalinterviewcoveringsystemdesign,failuremodes,andtrade-offs.
• Finaldiscussionfocusedonownership,reliabilitymindset,andexecutionstyle.

Weavoidprocesstheatre.Ifyoucandesignsystemsthatdon'tfallapartunderpressure,we'llmovefast.