Sr AI Agent Engineer

Story Terrace Inc.; Bengaluru; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

LexsiLabs, a frontier AI lab, is building a high-autonomy AI engineering agent that can execute end-to-end workflows atop the Lexsi backend. The system reasons over objectives, plans actions, interacts with tools and data, evaluates outcomes, and iterates while remaining interpretable and aligned.

As a Sr AI Agent Engineer, you will define and build the core architecture, make foundational decisions on reasoning, memory, and execution, and own the system from day one in ambiguous environments.

Qualifications

• Significant experience building and shipping complex AI/ML systems.
• Hands-on experience with agentic AI systems and frameworks (e.g., ReAct, AutoGPT, LangChain).
• Strong backend fundamentals with Python and API development.
• Systems-thinking mindset about performance, reliability, safety, and interpretability.
• Comfort working in ambiguous, fast-moving environments.

Responsibilities

• Own the architecture and implementation of the AI Engineering Agent.
• Build robust tool orchestration and execution layers.
• Design memory and state management for long-running tasks.
• Embed alignment, safety, and interpretability in system design.
• Stress-test agent behavior in real-world conditions.
• Set a high engineering bar with ownership and accountability.

Skills

AI systems design

Agent engineering

Ownership & accountability

Ambiguity handling

Memory/state design

Tools

Python

APIs

Cloud platforms

Databases

Job description

LexsiLabsisafrontierAIlabfocusedonbuildingaligned,interpretable,andsafesuperintelligentsystems.Ourworkspansalignmentmethodologies,interpretability-ledsystemdesign,andfoundationalmodelresearchacrossstructured,tabular,andenterprisedata.WebuildAIsystemsintendedforreal-worlddeployment,wheretransparency,auditability,androbustnessarefirst-classconstraints.

Weoperatewithaflatstructure,highautonomy,andastrongbiastowardengineerswhotakefullownershipofwhattheybuild,fromarchitecturetoproductionbehavior.

TheRole

Wearebuildingahigh-autonomyAIEngineeringAgentthatcanexecuteend-to-endAIengineeringworkflowsontopoftheLexsibackend.Thesystemisdesignedtoreasonovercomplexobjectives,planmulti-stepactions,interactwithtoolsanddatasystems,evaluateoutcomes,anditerateoverlonghorizonswhileremaininginterpretableandaligned.

AsaSrAIAgentEngineer,youwillberesponsiblefordefiningandbuildingthecoreagentarchitecture.Youwillmakefoundationaldecisionsabouthowtheagentreasons,plansandexecutesactions,maintainsmemoryandstate,andhasitsdecisionsinspectedandexplained.Thisrolerequiresdeephands-onengineeringandtheabilitytooperateinambiguousenvironmentswithownershipfromdayone.

WhatYou’llBuild

• End-to-endAIEngineeringAgentsthatcanautonomouslyperformtaskssuchasexperimentdesign,evaluation,analysis,andreporting,ratherthanmerelyassistingahumanintheseworkflows.
• HarnessEngineering:Abletodesignandmaintaincomplexharnesscomponentsthatsupportagents'scaleexponentiallyforcomplextasks.
• Agentarchitecturesthatcombinereasoning,planning,toolorchestration,andmemory,withexplicithandlingoflong-horizonexecution,partialfailures,andself-correction.
• DeepintegrationswiththeLexsibackend,includinginternalevaluationsystems,datapipelines,andalignmenttooling,aswellasenterpriseAPIsandproprietarydatasources.
• Agentsdesignedforenterpriseandregulatedenvironments,whereeveryaction,decision,andoutputmustbeinspectable,explainable,anddefensible.

Responsibilities

• OwnthearchitectureandimplementationoftheAIEngineeringAgent,makingearlydesigndecisionsaroundplanners,reasoningloops,memorymodels,andexecutioncontrolthatwillshapethesystemlong-term.
• Buildrobusttoolorchestrationandexecutionlayers,ensuringtheagentcaninteractreliablywithinternalservices,externalAPIs,anddatasystems,andrecovergracefullyfromfailures.
• Designandimplementmemoryandstatemanagement,enablingagentstooperateacrosslong-runningtasks,retainrelevantcontext,andreasonoverpastactionsandoutcomes.
• Embedalignment,safety,andinterpretabilityintothesystemdesign,workingcloselywithresearchteamstoensurethatagentbehaviorisauditableandcontrollablebyconstruction.
• Stress-testagentbehaviorinreal-worldconditions,identifyingedgecases,failuremodes,anddistributionshifts,anditeratingonthesystemtoimprovereliabilityandcorrectness.
• Setahighengineeringbar,contributingtodesigndiscussions,codereviews,andtechnicaldecision-makingwithastrongsenseofownershipandaccountability.

Requirements

• SignificantexperiencebuildingandshippingcomplexAIorML-heavysystems,whereyouhaveownedarchitectureandseensystemsevolveinproduction,notjustprototypes.
• Hands-onexperiencewithagenticAIsystemsandframeworks,suchasReAct-styleagents,AutoGPT-likesystems,LangChain,LangGraph,SemanticKernel,orsimilar,withaclearunderstandingoftheirlimitationsandfailuremodes.
• Strongbackendengineeringfundamentals,includingadvancedPythonproficiency,experiencebuildingAPIsandservices,andfamiliaritywithdatabases,datapipelines,andcloudinfrastructure.
• Asystems-thinkingmindset,withtheabilitytoreasonaboutperformance,reliability,cost,safety,andinterpretabilityasinterconnecteddesignconstraints.
• Comfortworkinginambiguous,fast-movingenvironments,whereproblemsarelooselyspecifiedandownershipisexpectedratherthanassigned.

StrongBonusSignals

• Experiencebuildinglong-horizonorstatefulagentsystemsthatmustreasonovertimeratherthansingle-turninteractions.
• PriorexposuretoAIalignment,interpretability,orsafetytooling,especiallyinproductionorenterprisesettings.
• Experienceworkinginregulatedorhigh-stakesdomains,wheresystembehaviormustbeexplainedandauditedafterdeployment.
• Atrackrecordofdebuggingandimprovingsystemsthatbehavedunpredictablyintherealworld.

Wemovequicklyandexpectcandidatestodothesame.Wevaluesubstanceoverpolishandexecutionoverrhetoric.