Role: Leverage AI/ML to optimize load testing, scalability analysis, and bottleneck detection. Requirements Design AI-enhanced performance tests using any of Performance test tools like (JMeter/ Blazemeter/ k6/ Locust) with realistic traffic simulation using ML models. Implement AI for: Predictive scaling (forecast infrastructure needs from historical data). Root cause analysis (auto-correlate metrics like latency/CPU to pinpoint issues). Self-tuning tests (dynamically adjust load parameters based on system behavior). Integrate with observability stacks (Grafana/Prometheus) + AIOps tools (Dynatrace, Datadog) Analyze logs/metrics using NLP/ML (e.g., cluster error patterns automatically). Work with CI/CD pipelines (Jenkins, GitHub Actions) for AI-driven test execution. Required Skills: Strong performance testing in any Performance test tools (JMeter, Blazemegter, k6). Python/Go for AI/analytics (e.g., Pandas, TensorFlow for metrics analysis). Cloud load testing (AWS/Azure Load Testing).
Role: Build AI-powered chatbots using Python and NLP technologies. Requirements Develop AI chatbots using Python with frameworks like LangChain, Rasa, or OpenAI s ChatGPT API. Implement Natural Language Processing (NLP) for intent recognition and response generation. Integrate AIaIntegrate chatbots with messaging platforms (Slack, WhatsApp, Telegram) or web apps agents with databases, APIs, and external tools for real-world applications. Use LLMs (GPT, Claude, Gemini, or open-source models) for conversational AI. Improve chatbot performance through fine-tuning & prompt engineering. Implement memory modules and session logic to manage multi-turn, contextual conversations. Required Skills: Strong Python programming (APIs, async, Flask/FastAPI) Experience with chatbot frameworks (LangChain, Rasa, Dialogflow) Knowledge of LLM-based chatbots (OpenAI, Claude, Gemini, or Llama 3) Working knowledge of NLP concepts such as tokenization, embeddings, and intent detection Familiarity with REST APIs & webhooks Good to Have (Added Advantage): Experience with voice-based chatbots (Speech-to-Text, Text-to-Speech) Knowledge of vector databases (for chatbot memory) Deployment on cloud platforms (AWS Lambda, GCP, Azure Bot Service)
Requirements 1 2 years of experience in CAM/Tax/Insurance Reconciliation, CAM/Desktop Audit, sending estoppel, financial, insurance requests to Tenants or Landlord in real estate industry. Need experience in tracking key dates and amounts from lease documents in Lease administration tools. Experience in amendment abstraction/tracking move-ins and move-outs of tenants. Hands on Experience in Lease administration tools like Yardi, JDE, Visual Lease, etc. Excellent understanding of Real Estate terminologies and concepts. Should be a self-starter with high initiative and enthusiastic to learn and deliver on latest tools and technologies. Strong technical background and have excellent problem-solving abilities. Should possess self-motivated interest to learn and deploy new initiatives in the team. Excellent oral and written communication skills. Ability to express views regarding process or team. Should be a good team player with positive attitude. Required Skills: Should be a good team player with positive attitude. You have experience using Sketch and InVision or Framer X You have some previous experience working in an agile environment Think two-week sprints. You are familiar using Jira and Confluence in your workflow
Role: Develop AI agents that can perform tasks autonomously using Python and modern AI frameworks. Requirements Design and build AI agents that can automate workflows, make decisions, or interact with APIs. Use Python with AI libraries like LangChain, LlamaIndex, AutoGen, or OpenAI Assistants API to create functional agents. Integrate AI agents with databases, APIs, and external tools for real-world applications. Fine-tune agents using RAG (Retrieval-Augmented Generation) or function calling for better accuracy and responses. Optimize agent performance, handle errors, and ensure reliability. Work with LLMs (GPT, Claude, Gemini, or open-source models like Llama 3) to power agent logic Required Skills: Strong Python programming (OOP, async, APIs) Experience with AI agent frameworks (LangChain, AutoGen, CrewAI, etc.) Knowledge of LLM integration (OpenAI, Anthropic, Mistral, etc.) Familiarity with API interactions (REST, GraphQL Apply prompt engineering strategies to guide and control LLM outputs Good to Have (Added Advantage): Experience with RAG (Vector DBs like Pinecone, FAISS, Weaviate) Knowledge of vector databases (for chatbot memory) Deployment on cloud platforms (AWS Lambda, GCP, Azure Bot Service)
Role: Design and build advanced conversational AI agents that engage in human-like dialogue using Python and modern NLP/LLM technologies. Requirements Develop conversational AI agents that handle multi-turn dialogues, context retention, and personalized responses Use Python with frameworks like LangChain, AutoGen, Rasa, or OpenAI s Assistants API to build dialogue systems Integrate LLMs (GPT-4, Claude, Gemini, Llama 3) with speech-to-text/text-to-speech (TTS/STT) for voice-enabled agents (if needed) Implement memory & context management (e.g., using vector DBs like Pinecone or Redis) Optimize conversational flows using prompt engineering, fine-tuning, or RAG (Retrieval-Augmented Generation). Deploy agents on messaging platforms (Slack, WhatsApp, Teams) or voice assistants (Alexa, Google Assistant). Required Skills: Strong Python programming (async, APIs, Flask/FastAPI) Experience with AI agent frameworks (LangChain, AutoGen, CrewAI, etc.) Knowledge of LLM integration (OpenAI, Anthropic, Mistral, etc.) Familiarity with API interactions (REST, GraphQL Apply prompt engineering strategies to guide and control LLM outputs Good to Have (Added Advantage): Experience with RAG (Vector DBs like Pinecone, FAISS, Weaviate) Knowledge of vector databases (for chatbot memory) Deployment on cloud platforms (AWS Lambda, GCP, Azure Bot Service)