8 Cognitive Search Jobs

Acronotics Limited specializes in robotic process automation, artificial intelligence, and intelligent automation technologies. We build and implement cutting-edge robotic automation and AI solutions, leveraging human intelligence to create transformative products and services. As a specialist consulting and services firm, we focus on modern-age automation technologies such as RPA and AI. Our flagship product, Radium AI, automates bot monitoring and support, delivering frictionless digital worker support. We are committed to helping our clients design, develop, and implement game-changing automation solutions. This is a full-time on-site role for a Technical Architect (Azure AI + GenAI) located in Bengaluru. As the Technical Architect, you will be responsible for designing and implementing AI solutions using Azure AI and Generative AI technologies. Your primary task will involve designing the end-to-end system architecture for a GenAI based solution to query enterprise financial data from Power BI, OLAP Cubes, and documents. Additionally, you will define the Azure AI tech stack, data integrations, security protocols, and deployment pipeline, and oversee the actual implementation of this solution. Your key responsibilities will include defining the phased architecture covering Power BI, cubes, unstructured docs, web, and ML, selecting Azure components such as OpenAI, Cognitive Search, Synapse, and Logic Apps, ensuring scalability, security, and performance best practices, supporting cross-role coordination, mentoring technical leads, and aligning the solution with enterprise standards and data governance policies. To be successful in this role, you should have at least 5 years of experience in enterprise technical architecture, including GenAI use cases, expertise with the Azure AI ecosystem, API management, and LLM orchestration, and proven experience in designing multi-phase AI platforms. If you are passionate about leveraging cutting-edge technologies to drive innovation and automation, and have a strong background in technical architecture and AI solutions, we encourage you to apply for this exciting opportunity at Acronotics Limited.,

You will be joining Acronotics Limited, a company specializing in robotic process automation, artificial intelligence, and intelligent automation technologies. Your role as a Technical Architect (Azure AI + GenAI) will involve designing and implementing AI solutions utilizing Azure AI and Generative AI technologies. Specifically, you will be tasked with creating the system architecture for a GenAI based solution to access enterprise financial data from Power BI, OLAP Cubes, and various documents. Your responsibilities will include defining the Azure AI tech stack, data integrations, security protocols, and deployment pipeline, as well as overseeing the implementation of the solution. Your key responsibilities will involve defining a phased architecture that covers Power BI, cubes, unstructured docs, web, and machine learning. Additionally, you will be responsible for selecting Azure components such as OpenAI, Cognitive Search, Synapse, and Logic Apps, ensuring scalability, security, and performance best practices, supporting cross-role coordination, and mentoring technical leads. It will be essential to align the solution with enterprise standards and data governance policies. To be successful in this role, you should have at least 5 years of experience in enterprise technical architecture, with a focus on GenAI use cases. You should possess expertise in the Azure AI ecosystem, API management, and LLM orchestration, as well as a proven track record in designing multi-phase AI platforms. If you are passionate about leveraging cutting-edge technologies to create transformative products and services, and have a strong background in technical architecture and AI solutions, we encourage you to apply for this exciting opportunity at Acronotics Limited.,

As an AI Engineer specializing in Gen AI, NLP, and Python, you will be responsible for developing multiple product features utilizing Deep Learning, NLP, Graph analytics, Cognitive search, Image processing, Process Automation, LangGraph, and LangSmith. With 5 - 12 years of experience, you will leverage your expertise in Python and GenAI to scale the AI model capabilities effectively. Your role will involve working with Python Azure function, SQL DB, Cognitive search, Evaluation Metrics, RAGAS, and Advance RAG to enhance the functionalities and performance of AI models. You will collaborate with a team of professionals to design and implement innovative solutions that meet the requirements of the projects. This position is based in all LTIM Office Locations, offering you the opportunity to contribute to cutting-edge projects and make a significant impact in the field of Artificial Intelligence. If you are passionate about AI, have a strong background in Python, and possess a deep understanding of Gen AI and Deep Learning, we encourage you to apply and join our dynamic team.,

You are a highly skilled GenAI Solution Architect with over 10 years of experience, looking to lead the design and implementation of cutting-edge Generative AI (GenAI) and Large Language Model (LLM) solutions for enterprise environments. Your role involves leveraging Azure AI services to deliver scalable, secure, and responsible AI applications. Your responsibilities include architecting, designing, and implementing GenAI/LLM-based enterprise solutions. You will work hands-on with Azure OpenAI, Form Recognizer, Cognitive Search, and other Azure AI services. Leading the end-to-end solution lifecycle, you will collaborate with development teams and stakeholders to integrate GenAI capabilities into existing applications using .NET and Cosmos DB. Ensuring best practices in scalability, cost-efficiency, compliance, and responsible AI delivery is crucial. To excel in this role, you need a minimum of 10 years of experience in solution architecture, with at least 2 years in AI/ML or GenAI space. Strong expertise in Azure OpenAI Services, Document Intelligence (Form Recognizer), and Azure Cognitive Search is required. Familiarity with .NET programming and Cosmos DB is a plus. Your solid experience in prompt design, LLM orchestration, and deploying AI models at scale will be valuable. Your excellent communication, stakeholder management, and documentation skills will be essential for success in this role. Understanding secure, compliant, and cost-optimized AI solution delivery is also a key requirement.,

We are seeking a Generative AI Engineer with 712 years of experience for a 12-month hybrid engagement (2 days onsite) in Bengaluru, Chennai, Hyderabad, Pune, or Vadodara. The candidate will develop enterprise-grade, cloud-native GenAI applications leveraging Azure OpenAI, Azure Cognitive Services, Azure ML Studio, and Azure Document Intelligence. Proficiency in implementing LLMs, RAG pipelines, OCR, and agent-based frameworks using LangChain, LlamaIndex, and Semantic Kernel is critical. The engineer should have experience in deploying scalable AI solutions across production environments. This role demands a mix of technical depth and applied AI implementation with strong delivery ownership and a problem-solving mindset. Location - Bengaluru, Chennai, Hyderabad, Pune, Vadodara (Hybrid 2 days WFO)

Job Title: Senior Generative AI Developer (Lead - Data Science) Gurgaon / Noida | 7-10 Years Experience About the Role We are looking for an experienced Senior Generative AI Developer to lead the design, development, and deployment of large-scale enterprise-grade GenAI systems. This is a hybrid role requiring both deep hands-on expertise and strategic leadership , working across multi-cloud environments and managing the full lifecycle of AI/ML systems. Key Responsibilities Technical Leadership Architect multi-LLM systems (e.g., Mixture-of-Experts, LLM routing) for performance-cost optimization. Design and scale training pipelines using FSDP, DeepSpeed on GPU/TPU clusters. Cloud-Native AI Development Build and manage multi-cloud GenAI platforms (Azure OpenAI, GCP Vertex AI, AWS Bedrock) with unified MLOps. Implement enterprise-grade security: VPC peering, private endpoints , and regulatory compliance (e.g., data residency). Innovation & Strategy Drive pioneering initiatives such as Agentic workflows , real-time fine-tuning, and synthetic data generation . Define and execute AI governance : model cards, drift monitoring, red-teaming protocols. Cross-Functional Impact Collaborate with product and business teams to define GenAI strategy and ROI metrics (e.g., automation cost savings). Mentor junior engineers and promote GenAI best practices across the organization. Required Qualifications Education : Bachelors/Master’s in CS, AI/ML, or equivalent experience. Experience : 5+ years in ML, 2+ years specifically in Generative AI. Technical Mastery Languages : Expert in Python Frameworks : PyTorch, TensorFlow Extended (TFX), ONNX Runtime Certifications : Azure AI Engineer Expert, GCP ML Engineer (preferred) GenAI Expertise Experience shipping production-scale GenAI systems (e.g., 10k+ QPS chatbots, GitHub Copilot-scale models). Mastery of advanced LLM techniques (LLM orchestration, guardrails, self-reflective prompting). Must-Have Experience Azure : Azure OpenAI, MLOps Pipelines, Cognitive Search GCP : Vertex AI Evaluation, Gemini Multimodal, TPU v5 Pods Built RAG systems using hybrid search (vector + keyword) and real-time data hydration Led AI compliance in regulated domains (finance, healthcare) Preferred Additions Experience with multi-cloud GenAI deployments (e.g., training on GCP, serving on Azure). Certification in Azure and/or GCP AI tracks. Exposure to autonomous agents, vector databases , and AI-driven business automation.

Job Title: Python AI/ML Engineer Location: Gurugram Experience: 5 to 8 years Job Summary: We are looking for a passionate and skilled Python AI/ML Engineer who brings strong expertise in building AI/ML solutions, productionizing models, and contributing to end-to-end ML pipelines. The ideal candidate should possess deep knowledge of traditional and deep learning concepts, hands-on programming capabilities, experience in enterprise-grade software engineering, and a good understanding of MLOps practices. Key Responsibilities: Design, develop, and deploy scalable machine learning models for classification, regression, NLP, and generative tasks. Build and optimize data transformation workflows using Python and Pandas. Lead AI/ML project pipelines from data ingestion to model deployment and monitoring. Implement model observability, monitoring for drift, and continuous model evaluation. Develop REST APIs and integrate ML models with production systems using frameworks like FastAPI. Participate in code reviews, write unit/integration tests, and ensure high code quality. Collaborate with cross-functional teams including Data Engineers, DevOps, and Product Managers. Stay current with the latest developments in AI, GenAI, ML frameworks, and tools. Use DevOps/MLOps tools to automate and manage model lifecycle processes. Required Skills: Programming & Python Ecosystem: Advanced proficiency in Python, including libraries such as Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch. Strong understanding of asynchronous programming, FastAPI, and concurrency (Starlette). Deep understanding of multithreading, multiprocessing, and the Python GIL. Ability to write clean, efficient, and testable code. Machine Learning & Deep Learning: Solid grasp of traditional ML concepts: classification, regression, overfitting/underfitting, regularization (L1/L2), multicollinearity. Experience with deep learning: RNNs, attention mechanisms, dropout, early stopping, loss functions (BCE, categorical cross entropy), diffusion models vs GANs. Familiarity with transfer learning and pre-trained model fine-tuning. MLOps: Understanding of ML pipeline design including model training, deployment, and monitoring. Experience in detecting and mitigating data drift and concept drift. Exposure to model observability, monitoring unstructured data drift, and automated drift alerts. Software Engineering & DevOps: Strong skills in REST API development, integration testing, and CI/CD practices. Experience with containerization tools like Docker. Familiarity with cloud-based ML deployment (AWS/Azure) and logging frameworks. Hands-On Problem Solving & Data Engineering: Ability to perform data transformation and aggregation using Python/Pandas. Experience handling dataframes, joins, ranking, filtering, mapping, and custom logic for preprocessing tasks. Nice-to-Have: Experience in GenAI and working with LLMs. Exposure to tools like MLflow, Kubeflow, Airflow, or similar MLOps platforms. Understanding of NLP, embeddings, and transformer-based models. Prior contributions to open-source ML tools or GitHub repositories.

Generative AI Engineer Overview We are seeking a visionary GenAI Engineer to lead the design and development of next-generation AI applications using advanced AI services. The ideal candidate will bring deep expertise in GenAI technologies, including Retrieval-Augmented Generation (RAG), intelligent agents, and model fine-tuning, coupled with hands-on experience using tools like LangChain, Model Context Protocol, and Azures full AI stack. Task and Responsibilities: Implement end-to-end Generative AI solutions on the Azure Cloud Platform, leveraging services such as: Azure OpenAI Service, Azure AI Search, Azure Cognitive Services, Azure AI Foundry, Azure Machine Learning etc. Creating data pipelines to ingest, process, and prepare data for analysis and modeling using Azure services, such as Azure AI Document Intelligence , Azure Databricks etc. Design and deploy RAG pipelines, incorporating structured and unstructured data to enhance LLM-based applications. Develop and orchestrate AI Agents and Autonomous Agents for real-time decision-making, task and automation. Fine-tune and optimize Small Language Models ( SLMs ) for domain-specific applications with a focus on performance, cost, and inference latency. Integrate LLMs/SLMs into applications using frameworks such as LangChain , Model Context Protocol ( MCP ), etc. Collaborate with data scientists, ML engineers, and product teams to align AI capabilities with business goals. Lead technical discussions and create architecture blueprints, best practices, and governance models for GenAI adoption across the enterprise. Monitor and optimize deployed solutions for scalability, latency, security, and compliance. Qualifications: Bachelor's or master's degree in computer science, Data Science, AI/ML, information technology, or a related field. Overall 8+ years’ combined experience in IT, 5+ years of experience in AI/ML solution engineering with at least 2+ years focused on Generative AI. Strong experience with LLMs and SLMs, including integration of open source models, prompt engineering, evaluation, and fine-tuning techniques. Proven track record using LangChain, Semantic Kernel, RAG, AI Agents, and MCP (Model Context Protocol) in production environments. Solid understanding and Hands-on experience with vector databases, embeddings, and Azure AI Search integration for semantic retrieval. Hands-on experience with tools like MLFlow, Azure Machine Learning, Azure OpenAI Service, Azure AI Search, Azure Cognitive Services, Azure AI Foundry, Azure Machine Learning etc. Familiarity with MLOps, CI/CD pipelines, and responsible AI practices. Experience deploying AI models on Azure Kubernetes Services (AKS) or Azure Container Apps. Understanding of security and compliance in AI deployments (e.g., data privacy, bias detection). Proficiency in programming languages like Python (essential). Excellent problem-solving, analytical, and critical thinking skills. Strong communication and collaboration skills to work effectively in a team environment. A passion for innovation and a desire to push the boundaries of what's possible with Gen AI. Relevant industry certifications, such as Microsoft Certified: Azure AI Engineer, Azure Solution Architect etc. is a plus.