Sr AI Agent Engineer

Lexsi Labs; Bengaluru; In loco; INR 4.000.000 - 6.500.000; Tempo pieno

Descrizione del lavoro

LexsiLabs in Bengaluru is building a high-autonomy AI Engineering Agent. As a Sr AI Agent Engineer you will define and build the core agent architecture, making foundational decisions about reasoning, planning, memory, and execution with observable state.

This role demands hands-on engineering, strong Python backend skills, API and data-pipeline experience, and familiarity with agentic AI frameworks such as ReAct and LangChain.

Competenze

• Significant experience building and shipping complex AI/ML-heavy systems.
• Hands-on experience with agentic AIsystems and frameworks.
• Strong backend fundamentals with Python, APIs, and data pipelines.
• Systems thinking mindset for performance, reliability, safety, and interpretability.
• Comfort working in ambiguous, fast-moving environments.

Mansioni

• Own the architecture and implementation of the AIEngineeringAgent.
• Build robust tool orchestration and execution layers.
• Embed alignment, safety, and interpretability into system design.
• Stress-test agent behavior in real-world conditions.
• Set a high engineering bar and contribute to design discussions.

Conoscenze

Backend engineering

Python

Agentic AI systems

Workflow orchestration

Distributed systems

Strumenti

LangChain

LangGraph

Semantic Kernel

API development

Cloud infrastructure

Descrizione del lavoro

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

Weoperatewithaflatstructure,highautonomy,andastrongbiastowardengineerswhotakefullownershipofwhattheybuild,fromarchitecturetoproductionbehavior.

TheRole

Wearebuildinga high-autonomyAIEngineeringAgent thatcanexecuteend-to-endAIengineeringworkflowsontopoftheLexsibackend.Thesystemisdesignedtoreasonovercomplexobjectives,planmulti-stepactions,interactwithtoolsanddatasystems,evaluateoutcomes,anditerateoverlonghorizonswhileremaininginterpretableandaligned.

Asa SrAIAgentEngineer ,youwillberesponsiblefordefiningandbuildingthecoreagentarchitecture.Youwillmakefoundationaldecisionsabouthowtheagentreasons,plansandexecutesactions,maintainsmemoryandstate,andhasitsdecisionsinspectedandexplained.Thisrolerequiresdeephands-onengineeringandtheabilitytooperateinambiguousenvironmentswithownershipfromdayone.

WhatYou'llBuild

• End-to-endAIEngineeringAgents thatcanautonomouslyperformtaskssuchasexperimentdesign,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.
• 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

• Experiencebuilding long-horizonorstatefulagentsystems thatmustreasonovertimeratherthansingle-turninteractions.
• Priorexposureto AIalignment,interpretability,orsafetytooling ,especiallyinproductionorenterprisesettings.
• Experienceworkingin regulatedorhigh-stakesdomains ,wheresystembehaviormustbeexplainedandauditedafterdeployment.
• Atrackrecordofdebuggingandimprovingsystemsthatbehavedunpredictablyintherealworld.
  

Wemovequicklyandexpectcandidatestodothesame.Wevaluesubstanceoverpolishandexecutionoverrhetoric.