5 Cloud Ai Jobs

Senior Full Stack Developer Experience: 3-5 Years Exp Salary : 15 to 25 LPA Preferred Notice Period: Within 30 Days Shift: 10:00AM to 7:00PM IST Opportunity Type: Hybrid (Pune) Placement Type: Permanent (*Note: This is a requirement for one of Uplers' Clients) Must have skills required : Generative AI, Cloud AI Services, Architecture Inferenz(One of Uplers' Clients) is Looking for: Senior Full Stack Developer who is passionate about their work, eager to learn and grow, and who is committed to delivering exceptional results. If you are a team player, with a positive attitude and a desire to make a difference, then we want to hear from you. About Inferenz At Inferenz, our team of innovative technologists and domain experts help accelerating the business growth through digital enablement and navigating the industries with data, cloud and AI services and solutions. We dedicate our resources to increase efficiency and gain a greater competitive advantage by leveraging various next generation technologies. Our technology expertise has helped us delivering the innovative solutions in key industries such as Healthcare & Life Sciences, Consumer & Retail, Financial Services and Emerging industries. About The Role: Job Description: Role Overview: We are seeking an experienced Senior Full Stack Developer to join our team building innovative Generative AI (GenAI) based applications. The ideal candidate will have a strong background in developing scalable RESTful APIs using Python, as well as modern frontend applications with Node.js or React. Experience with cloud platforms (Azure or AWS), Kubernetes, microservices architecture, and version control (Git or Azure Repos) is essential. Familiarity with AI/ML/GenAI technologies and Agenting AI is highly valued. Key Responsibilities: Full-Stack Development: Design, build, and maintain scalable RESTful APIs using Python and frontend applications using Node.js or React. GenAI Integration: Develop and optimize Agenting AI components using Python, ensuring seamless integration with backend services. Cloud Deployment: Manage application deployment, scaling, and monitoring on Azure or AWS using Kubernetes and microservices architecture. Collaboration: Work with cross-functional teams using Jira and Confluence for project tracking and documentation. Performance Optimization: Ensure high availability, security, and efficiency of applications through robust coding practices and infrastructure management. Required Skills & Experience: Backend: Strong expertise in Python and REST API development. Frontend: Proficiency in Node.js, React, and modern JavaScript frameworks. Cloud & DevOps: Hands-on experience with Azure or AWS, Kubernetes, microservices, and Git or Azure Repos for version control. Tools: Familiarity with Jira, Confluence, and CI/CD pipelines. Experience: 5+ years in full-stack development with production-grade applications. Preferred Skills: AI/ML Knowledge: Understanding of GenAI tools (e.g., LangChain, LLMs, RAG/GraphRAG/MCP architectures) and Agenting AI development. Cloud AI Services: Experience with cloud-based AI platforms (e.g., AWS Bedrock, Azure AI). Architecture: Proficiency in designing scalable systems and troubleshooting distributed environments. What We Offer: Competitive salary and comprehensive benefits package. Flexible work hours and a hybrid working model to support work-life balance. Opportunities for professional growth and development in a cutting-edge technology environment. Exposure to Generative AI and other advanced technologies. Inferenz is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. How to apply for this opportunity: Easy 3-Step Process: 1. Click On Apply! And Register or log in on our portal 2. Upload updated Resume & Complete the Screening Form 3. Increase your chances to get shortlisted & meet the client for the Interview! About Our Client: At Inferenz, our team of innovative technologists and domain experts help accelerating the business growth through digital enablement and navigating the industries with data, cloud and AI services and solutions. We dedicate our resources to increase efficiency and gain a greater competitive advantage by leveraging various next generation technologies. Our technology expertise has helped us delivering the innovative solutions in key industries such as Healthcare & Life Sciences, Consumer & Retail, Financial Services and Emerging industries.. About Uplers: Our goal is to make hiring and getting hired reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant product and engineering job opportunities and progress in their career. (Note: There are many more opportunities apart from this on the portal.) So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Key Responsibilities Architecture Development Define and implement AI architecture for enterprise applications. Develop AI frameworks and models that integrate with existing enterprise systems . Ensure AI solutions are scalable, secure, and compliant with data privacy regulations (GDPR, CCPA, etc.) . Technical Leadership & Innovation Architect AI-powered platforms that support Gen-AI & AI frameworks and models. Stay ahead of AI advancements and drive innovation in AI-driven automation, personalization, and optimization . AI Model Development & Optimization Execute the training, fine-tuning, and deployment of LLMs and ML models. Optimize model performance using techniques such as prompt engineering, retrieval-augmented generation (RAG), and knowledge distillation . Implement MLOps and AIOps best practices for continuous model monitoring and improvement. Cloud & Infrastructure Integration Design and deploy AI solutions on Azure AI, AWS SageMaker, Google Vertex AI, or OpenAI services . Ensure AI applications are cloud-native, containerized (Docker, Kubernetes), and scalable . Implement data pipelines, feature stores, and vector databases for efficient AI processing. Cross-Functional Collaboration Work closely with engineering, data science, product, and business teams to align AI initiatives with company goals. Provide technical mentorship and guidance to AI engineers and developers. Communicate AI strategy and roadmaps to senior leadership and stakeholders. Security, Compliance & Responsible AI Ensure AI solutions adhere to ethical AI principles, bias mitigation, and fairness . Implement AI governance frameworks for explainability, accountability, and security. Address risks related to AI hallucinations, adversarial attacks, and regulatory compliance . Qualifications Educational qualification: B-Tech / M-Tech Computer Science preferred Experience : 10+ Years Mandatory/requires Skills : Core AI & GenAI Expertise Strong hands-on experience with LLMs (GPT, Llama, Claude, etc.), ML frameworks (TensorFlow, PyTorch, Hugging Face), and deep learning models . Expertise in GenAI applications, including chatbots, code generation, multimodal AI, and synthetic data generation . Experience with RAG, vector databases (FAISS, Pinecone, Weaviate), and embeddings . Proficiency in AI-driven knowledge management, summarization, and automation . Software Architecture & Engineering Strong understanding of enterprise software architectures, microservices, APIs, and distributed computing . Hands-on experience with Python, Java, Go, or other relevant languages . Familiarity with GraphQL, REST APIs, and event-driven architectures . Experience with MLOps pipelines, CI/CD for AI, and automated AI workflows . Cloud & DevOps Expertise in deploying AI models on Azure, AWS, or Google Cloud . Experience with serverless AI architecture, Kubernetes, and cloud-native AI . Knowledge of data engineering, data lakes, and streaming analytics for AI . Preferred Skills : Leadership & Communication Ability to translate complex AI concepts into business-friendly insights. Strong stakeholder management, presentation, and decision-making skills.

Join a company that is pushing the boundaries of what is possible. We are renowned for our technical excellence and leading innovations, and for making a difference to our clients and society. Our workplace embraces diversity and inclusion its a place where you can grow, belong and thrive. Your day at NTT DATA We are seeking a talented AI/GenAI Engineer to join our team in delivering cutting-edge AI solutions to clients. The successful candidate will be responsible for implementing, developing, and deploying AI/GenAI models and solutions on cloud platforms. This role requires knowledge of ServiceNow modules like CSM and virtual agent development. Candidate should have strong technical aptitude, problem-solving skills, and the ability to work effectively with clients and internal teams. What youll be doing Key Responsibilities: Cloud AI Implementation: Implement and deploy AI/GenAI models and solutions using various cloud platforms (e.g., AWS SageMaker, Azure ML, Google Vertex AI) and frameworks (e.g., TensorFlow, PyTorch, LangChain, Vellum). Build Virtual Agent in SN Design, develop and deploy virtual agents using SN agent builder Integrate SN Design and develop seamless integration of SN with other external AI systems Agentic AI: Assist in developing agentic AI systems on cloud platforms, enabling autonomous decision-making and action-taking capabilities in AI solutions. Cloud-Based Vector Databases: Implement cloud-native vector databases (e.g., Pinecone, Weaviate, Milvus) or cloud-managed services for efficient similarity search and retrieval in AI applications. Model Evaluation and Fine-tuning: Evaluate and optimize cloud-deployed generative models using metrics like perplexity, BLEU score, and ROUGE score, and fine-tune models using techniques like prompt engineering, instruction tuning, and transfer learning. Security for Cloud LLMs: Apply security practices for cloud-based LLMs, including data encryption, IAM policies, and network security configurations. Client Support Support client engagements by implementing AI requirements and contributing to solution delivery. Cloud Solution Implementation: Build scalable and efficient cloud-based AI/GenAI solutions according to architectural guidelines. Cloud Model Development: Develop and fine-tune AI/GenAI models using cloud services for specific use cases, such as natural language processing, computer vision, or predictive analytics. Testing and Validation Conduct testing and validation of cloud-deployed AI/GenAI models, including performance evaluation and bias detection. Deployment and Maintenance Deploy AI/GenAI models in production environments, ensuring seamless integration with existing systems and infrastructure. Cloud Deployment Deploy AI/GenAI models in cloud production environments and integrate with existing systems. Education Bachelor/Masters in Computer Science, AI, ML, or related fields. Experience 3-5 years of experience in engineering solutions, with a track record of delivering Cloud AI solutions. . Should have at least 2 years experience of SN and SN agent builder Technical Skills: Proficiency in cloud AI/GenAI services and technologies across major cloud providers (AWS, Azure, GCP) Experience with cloud-native vector databases and managed similarity search services Experience with SN modules like CSM and virtual agent builder Experience with security measures for cloud-based LLMs, including data encryption, access controls, and compliance requirements Programming Skills: Strong programming skills in languages like Python or R Cloud Platform Knowledge: Strong understanding of cloud platforms, their AI services, and best practices for deploying ML models in the cloud Communication Excellent communication and interpersonal skills, with the ability to work effectively with clients and internal teams. Problem-Solving Strong problem-solving skills, with the ability to analyse complex problems and develop creative solutions. Nice to have: Experience with serverless architectures for AI workloads Nice to have: Experience with ReactJS for rapid prototyping of cloud AI solution frontends Location: Delhi or Bangalore (with remote work options)

Your day at NTT DATA Cloud AI/GenAI Engineer(ServiceNow) We are seeking a talented AI/GenAI Engineer to join our team in delivering cutting-edge AI solutions to clients. The successful candidate will be responsible for implementing, developing, and deploying AI/GenAI models and solutions on cloud platforms. This role requires knowledge of ServiceNow modules like CSM and virtual agent development. Candidate should have strong technical aptitude, problem-solving skills, and the ability to work effectively with clients and internal teams. What youll be doing Key Responsibilities: Cloud AI Implementation: Implement and deploy AI/GenAI models and solutions using various cloud platforms (e.g., AWS SageMaker, Azure ML, Google Vertex AI) and frameworks (e.g., TensorFlow, PyTorch, LangChain, Vellum). Build Virtual Agent in SN Design, develop and deploy virtual agents using SN agent builder Integrate SN Design and develop seamless integration of SN with other external AI systems Agentic AI: Assist in developing agentic AI systems on cloud platforms, enabling autonomous decision-making and action-taking capabilities in AI solutions. Cloud-Based Vector Databases: Implement cloud-native vector databases (e.g., Pinecone, Weaviate, Milvus) or cloud-managed services for efficient similarity search and retrieval in AI applications. Model Evaluation and Fine-tuning: Evaluate and optimize cloud-deployed generative models using metrics like perplexity, BLEU score, and ROUGE score, and fine-tune models using techniques like prompt engineering, instruction tuning, and transfer learning. Security for Cloud LLMs: Apply security practices for cloud-based LLMs, including data encryption, IAM policies, and network security configurations. Client Support Support client engagements by implementing AI requirements and contributing to solution delivery. Cloud Solution Implementation: Build scalable and efficient cloud-based AI/GenAI solutions according to architectural guidelines. Cloud Model Development: Develop and fine-tune AI/GenAI models using cloud services for specific use cases, such as natural language processing, computer vision, or predictive analytics. Testing and Validation Conduct testing and validation of cloud-deployed AI/GenAI models, including performance evaluation and bias detection. Deployment and Maintenance Deploy AI/GenAI models in production environments, ensuring seamless integration with existing systems and infrastructure. Cloud Deployment Deploy AI/GenAI models in cloud production environments and integrate with existing systems. Education Bachelor/Masters in Computer Science, AI, ML, or related fields. Experience 3-5 years of experience in engineering solutions, with a track record of delivering Cloud AI solutions. . Should have at least 2 years experience of SN and SN agent builder Technical Skills: Proficiency in cloud AI/GenAI services and technologies across major cloud providers (AWS, Azure, GCP) Experience with cloud-native vector databases and managed similarity search services Experience with SN modules like CSM and virtual agent builder Experience with security measures for cloud-based LLMs, including data encryption, access controls, and compliance requirements Programming Skills: Strong programming skills in languages like Python or R Cloud Platform Knowledge: Strong understanding of cloud platforms, their AI services, and best practices for deploying ML models in the cloud Communication Excellent communication and interpersonal skills, with the ability to work effectively with clients and internal teams. Problem-Solving Strong problem-solving skills, with the ability to analyse complex problems and develop creative solutions. Nice to have: Experience with serverless architectures for AI workloads Nice to have: Experience with ReactJS for rapid prototyping of cloud AI solution frontends Location: Delhi or Bangalore (with remote work options)

Key Responsibilities: Cloud AI Design and Development: Design, develop, and deploy AI/GenAI models and solutions using various cloud platforms (e.g., AWS SageMaker, Azure ML, Google Vertex AI) and frameworks (e.g., TensorFlow, PyTorch, LangChain, Vellum). Agentic AI: Develop and integrate agentic AI systems on cloud platforms, enabling autonomous decision-making and action-taking capabilities in AI solutions. Cloud-Based Vector Databases: Design and implement cloud-native vector databases (e.g., Pinecone, Weaviate, Milvus) or cloud-managed services for efficient similarity search and retrieval in AI applications. Model Evaluation and Fine-tuning: Evaluate and optimize cloud-deployed generative models using metrics like perplexity, BLEU score, and ROUGE score, and fine-tune models using techniques like prompt engineering, instruction tuning, and transfer learning. Security for Cloud LLMs: Implement robust security measures for cloud-based LLMs, including data encryption, IAM policies, network security, model watermarking, and compliance with cloud security best practices. Technical Leadership: Provide technical guidance and support to junior team members on cloud AI implementation, ensuring high-quality deliverables and adherence to best practices. Client Engagement: Collaborate with clients to understand their AI requirements, develop tailored solutions, and deliver high-quality results. Cloud Solution Architecture: Design scalable, efficient, and cost-effective cloud-based AI/GenAI architectures, considering factors like data quality, model performance, and serverless/container-based deployment options. Cloud Model Development: Develop and fine-tune AI/GenAI models using cloud services for specific use cases, such as natural language processing, computer vision, or predictive analytics. Testing and Validation: Ensure thorough testing and validation of AI/GenAI models, including performance evaluation, bias detection, and explainability. Deployment and Maintenance: Deploy AI/GenAI models in production environments, ensuring seamless integration with existing systems and infrastructure. Knowledge Sharing: Share knowledge and expertise with the team, contributing to the development of best practices and staying up-to-date with industry trends. Requirements: Education: Bachelor/Master's in Computer Science, AI, ML, or related fields. Experience: 8+ years of experience in engineering solutions, with a track record of delivering Cloud AI solutions. Technical Skills: Proficiency in cloud AI/GenAI services and technologies across major cloud providers (AWS, Azure, GCP) Experience with cloud-native vector databases and managed similarity search services Experience with security measures for cloud-based LLMs, including data encryption, access controls, and compliance requirements Programming Skills: Strong programming skills in languages like Python or R Cloud Platform Knowledge: Strong understanding of cloud platforms, their AI services, and best practices for deploying ML models in the cloud Communication: Excellent communication and interpersonal skills, with the ability to work effectively with clients and internal teams. Problem-Solving: Strong problem-solving skills, with the ability to analyse complex problems and develop creative solutions. Nice to have: Experience with serverless architectures for AI workloads Nice to have: Experience with ReactJS for rapid prototyping of cloud AI solution frontends