Company Overview :
IRISS, Inc. is a leading innovator in the field of advanced technological solutions, providing cutting-edge products and services to enhance safety, reliability, and efficiency of assets across various industries. Our commitment to pushing boundaries and delivering exceptional solutions has positioned us as a trusted partner for clients seeking top-tier technical expertise in Condition Based Monitoring.
IRISS Inc - Leader in Electrical Maintenance Safety Solutions
IRISS - YouTube
Position : AI Engineer (Conversational Analytics & GenAI Systems)
Location : Bengaluru, India
About the Product :
You will work on IRISS's conversational analytics platform, a GenAI-powered chatbot that
transforms natural language queries into validated, compliant, and tenant-aware SQL and
visual insights. This platform enables users to ask business questions like “Show me last
month's motor temperature anomalies in Plant 3” and get immediate, accurate dashboards
and reports generated safely through AI-driven data pipelines.
Our AI stack :
- Interprets user intent using LLMs.
- Generates validated, policy-compliant SQL.
- Executes and visualizes data with context and feedback loops.
- Powers a RAG-based (Retrieval-Augmented Generation) framework integrated with
existing IoT and analytics microservices
Job Overview :
You will design, develop, and maintain the AI chatbot platform that serves as the
intelligence layer for our SaaS ecosystem. This includes architecting end-to-end
conversational pipelines from LLM prompt design to data retrieval, integrating vector-
based search systems and RAG pipelines into our service mesh, leveraging AWS AI / ML and
orchestration services such as Bedrock, Kendra, OpenSearch, Lambda, ECS, and S3 to build
scalable and secure infrastructure, and partnering with full-stack and front-end engineers
to embed AI features directly into user workflows
Backend :
ASP.NET Core with ABP & ASP.NET Zero modules, EF Core, and SQL Server for tenancy-aware domain logic
Python (FastAPI / Flask) for new microservices and migration targetsAPIs : SignalR hubs and REST endpoints exposed through the Web HostInfrastructure :AWS Services : ECS for container orchestration, RDS (Aurora) for databases, S3 forstorage, Lambda for serverless functions
Hangfire for background jobs, log4net + custom middleware for correlation-awarelogging
HealthChecks, Stripe + Firebase integrationsDevOps : AWS CDK-driven Infrastructure as Code with containerized services, Rediscaching, and microservice extensions
Frontend :
Angular 18 (latest version with standalone components support)TypeScript 5.5RxJS 7.4 for reactive programmingPrimeNG, Angular Material, ngx-charts for UI componentsKey Responsibilities :
Design and implement backend services in .NET Core (ASP.NET Core Web API) usingEntity Framework Core and LINQ
Help migrate our backend APIs to Python microservices architectureBuild clean, testable Angular 18+ UIs and reusable components (standalone)Design and evolve multi-tenant backend services for assets, sensors, work orders,notifications, and AI workflows
Integrate data sources : SQL (SQL Server / Aurora) and InfluxDB for time-series telemetryImplement background jobs, rate limiting, and observability using Hangfire, Redis, and logenrichment patterns
Extend REST and SignalR endpoints while maintaining tenant isolation and role-basedaccess control
Collaborate with IoT and data teams to expose sensor data, alerts, reports, and analyticsImplement authentication / authorization, input validation, and error handling across thestack
Participate in code reviews, ADRs, grooming, and release readiness checksContribute to CI / CD pipelines (GitHub Actions), basic observability, and performanceprofiling
Define service boundaries, transactional integrity, and performance within coreapplication layers
Core Stack & Technologies
AI / ML & Data Intelligence
Python 3.10+ (FastAPI, LangChain, Haystack, or equivalent)LLMs : OpenAI, Anthropic, Hugging Face, or open-source models (LLaMA, Mistral, Falcon)RAG Systems : FAISS, Pinecone, OpenSearch Vector Store, or ChromaDBPrompt Orchestration : LangChain, Semantic Kernel, or internal toolingData Validation & Safety : SQL sanitization layers and policy enforcement modulesVisualization Layer : Chart.js or D3.js integration for generated insightsCloud & Infrastructure :
AWS Bedrock, Kendra, OpenSearch, Lambda, S3, CloudWatch, ECS, and EC2API Gateway for AI microservicesRedis or DynamoDB for caching and conversation stateOpenTelemetry for observabilityCI / CD using GitHub Actions, AWS CDK, and Docker-based microservicesFront-End & Integration
Works closely with Angular 18+ applications and .NET / Python backend microservicesExposes APIs to the Full-Stack and Front-End teams for seamless user interactionsImplements real-time feedback mechanisms for model evaluation and tuningKey Responsibilities :
Architect, develop, and maintain the GenAI chatbot platform from the ground upBuild multi-turn conversation flows and contextual memory for data queriesImplement RAG pipelines using vector databases and curated embeddingsIntegrate open-source and commercial LLMs through APIs or local deploymentCreate safety and compliance modules that validate SQL and policy rules before executionCollaborate with backend engineers to design AI microservices that scale horizontallyDeploy, monitor, and optimize models using AWS Bedrock, Kendra, and OpenSearchMaintain observability and feedback loops for improving model accuracy and reliabilityPartner with front-end teams to deliver chat-first analytics interfacesContribute to documentation, testing, and architectural decision records for AI systemsRequirements :
Bachelor's or Master's degree in Computer Science, Data Science, or a related fieldMinimum 3 years of experience developing and deploying AI-powered applications orchatbots
Strong Python expertise (FastAPI, Flask, or Django for microservices)Experience with LLM integration (OpenAI, Bedrock, Hugging Face, or local models)Hands-on experience with AWS ecosystem including Bedrock, Kendra, OpenSearch, ECS,Lambda, and CloudWatch
Deep understanding of RAG architecture, vector databases, and embeddings-basedretrieval
Knowledge of prompt design, model orchestration, and AI safety validationFamiliarity with SQL and multi-tenant data systemsExperience with Docker, Git-based CI / CD, and microservice architecturesNice-to-Have
Experience fine-tuning or hosting open-source LLMs (LLaMA, Mistral, Falcon)Understanding of LangChain Agents or Semantic Kernel pipelinesFamiliarity with Angular and .NET ecosystems for end-to-end integrationExposure to observability frameworks such as OpenTelemetry, Prometheus, or GrafanaKnowledge of enterprise data governance and AI compliance frameworksContributions to open-source AI projects or custom LLM integrationsWhat You'll Work On :
Migration of .NET Core backend services to Python microservicesTenant-aware APIs powering asset hierarchies, predictive maintenance, and automatedwork orders
Real-time dashboards and notifications for sensor events, alerts, and chat integrationPerformance and reliability for data-heavy dashboards (pagination, caching, changedetection)
Background workflows orchestrating AI-driven insights and report exportsREST services consumed by Angular dashboards and mobile clientsObservability hooks (health checks, telemetry, correlation IDs) for enterprise-gradereliability
Developer experience improvements (codegen, linting, templates, better local envs)What You Will Build :
A conversational analytics chatbot capable of generating real-time, compliant SQL queriesRAG pipelines that fetch and embed domain knowledge across tenantsContext-aware AI microservices integrated with IRISS’s monitoring and reporting systemsEvaluation dashboards for prompt performance, latency, and query accuracyContinuous learning and feedback loops to improve the GenAI system over timeDevelopment Environment
Python 3.10+, FastAPI, LangChainAWS Bedrock, OpenSearch, Kendra, Lambda, ECSAngular 18+ for embedded UIsNode.js 16+, Yarn, VS CodeGitHub Actions and AWS CDK for CI / CDDockerized microservices architectureCompensation :
Competitive salary, benefits, and strong growth opportunities.