4 Rag Models Jobs

Introduction to IBM Software A career in IBM Software means you'll be part of a team that transforms our customer's challenges into solutions. Seeking new possibilities and always staying curious, we are a team dedicated to creating the world's leading AI-powered, cloud-native software solutions for our customers. Our renowned legacy creates endless global opportunities for our IBMers, so the door is always open for those who want to grow their career. IBM Intelligent Automation, powered by AI, addresses challenges by helping People become more productive, Businesses more scalable, and Systems more resilient. We combine human skills with automation and AI to enhance team productivity and improve decision-making. We help companies digitize and intelligently automate and connect their business processes and systems end-to-end to improve business outcomes at scale. We assure that all of the applications and systems businesses rely on are always on and perform cost-effectively to deliver the best possible user experience. IBM's product and technology landscape includes Research, Software, and Infrastructure. Entering this domain positions you at the heart of IBM, where growth and innovation thrive. Your Role and Responsibilities as a Client Adoption Specialist As a Client Adoption Specialist, you're responsible for engaging with IBM clients to accelerate their deployment of strategic offerings within their production environment, delivering deep technical expertise that leads to successful implementations. You will be assigned to work with strategic offerings that include IBM Concert, watsonx Code Assistant for Z, and watsonx Assistant for Z. You will work directly with the end client, planning for and executing implementation plans. You will collaborate with the assigned IBM account teams as they are responsible for ensuring the right client sponsors and champions are actively involved and, upon successful implementation, validating key performance measurements have been met. You will interact with IBM development labs to provide product feedback and engage as needed for product support. The core objectives and success factors for you and other team members are: Core ObjectivesSuccess FactorsAccelerate client adoption# Client AdoptersDrive future growth# Case StudiesIncrease platform stickiness# Client References Export to Sheets This role aligns with IBM Values Growth Minded, Trusted, Team Focused, Courageous, Resourceful, Outcome-Focused. Education Required Education: Bachelor's Degree Preferred Education: Bachelor's Degree Technical and Professional Expertise Strong skills are an imperative. The following skills and attitudes are critical to success in the role. Professional Skills Strong communication Intellectual curiosity / continuous learner Ability to influence Strong organizational skills Timely, execution for impact Proven track record to win and compete Change agent Technical Expertise Expert experience with two or more of the following:Operating system administration skills (Linux, Windows, zOS) TCP/IP network and LDAP administration skills APM solutions on IBM Z platform IBM CICS and/or IMS admin skills Enterprise COBOL development skills (e.g., read, write, modify, troubleshoot) Java development skills (e.g., read, write, modify, troubleshoot) Proficient experience with two or more of the following:OpenTelemetry (OTeL) Ansible Automation Platform Programming languages common to automation (e.g., REX, JCL, YAML) Working with Large Language Models and RAG models Working with Conversational AI Working with VS Code Interoperating COBOL and Java within a zOS subsystem is a bonus

Job Opportunity: ML Prompt Engineer Location: Bangalore (Hybrid) Experience: 5 to 12 Years Job Type: Full-Time CTC & Client: Will be discussed during the call Job Title: Principal Developer ML/Prompt Engineer Technologies: Amazon Bedrock, RAG Models, Java, Python, C/C++, AWS Lambda Responsibilities: -Develop, deploy, and maintain RAG models integrated with Amazon Bedrock. -Leverage models like Anthropic Claude to build scalable and secure GenAI applications. -Design intelligent prompts to improve the accuracy, alignment, and reliability of LLM outputs. -Build reusable prompt templates, libraries, and chains to accelerate GenAI development. -Collaborate with cross-functional teams to ensure application effectiveness and business alignment. -Monitor model performance, implement evaluations (manual & automated), and conduct A/B testing. -Address prompt injection risks and implement effective mitigation strategies. -Utilize DevOps tools, CI/CD pipelines, and agile methodologies for smooth deployment and integration. -Stay updated with advancements in LLM architectures, prompt engineering, and AI tooling. Required Skills & Qualifications: -5–12 years of experience in AI/ML or full-stack development environments. -Proficiency in Java, Python, or C/C++. -Hands-on experience with Amazon Bedrock, AWS Lambda, or similar cloud platforms (SageMaker, Comprehend). -Deep understanding of RAG architecture or tools like Pinecone, Ragna, etc. -Strong grasp of prompt engineering techniques (zero-shot, few-shot, CoT, prompt tuning, chaining). -Experience with GenAI ecosystems: Anthropic, OpenAI, Hugging Face, TensorFlow, PyTorch. -Familiarity with prompt evaluation, A/B testing, and structured prompt workflows. -Exposure to DevOps tools and Git. -Agile/Scrum experience; excellent team collaboration and communication skills. Apply now or reach out to learn more OR mailCV to anzia.sabree@bct-consulting.com

Job Title: ML Prompt Engineer Location - Bangalore Hybrid . Job Description: Principle Developer - ML/Prompt Engineer Technologies: Amazon Bedrock, RAG Models, Java, Python, C or C++, AWS Lambda Responsibilities: Responsible for developing, deploying, and maintaining a Retrieval Augmented Generation (RAG) model in Amazon Bedrock, our cloud-based platform for building and scaling generative AI applications. Design and implement a RAG model that can generate natural language responses, commands, and actions based on user queries and context, using the Anthropic Claude model as the backbone. Integrate the RAG model with Amazon Bedrock, our platform that offers a choice of high-performing foundation models from leading AI companies and Amazon via a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI. Optimize the RAG model for performance, scalability, and reliability, using best practices and robust engineering methodologies. Design, test, and optimize prompts to improve performance, accuracy, and alignment of large language models across diverse use cases. Develop and maintain reusable prompt templates, chains, and libraries to support scalable and consistent GenAI applications. Skills/Qualifications: Experience in programming with at least one software language, such as Java, Python, or C/C++. Experience in working with generative AI tools, models, and frameworks, such as Anthropic, OpenAI, Hugging Face, TensorFlow, PyTorch, or Jupyter. Experience in working with RAG models or similar architectures, such as RAG, Ragna, or Pinecone. Experience in working with Amazon Bedrock or similar platforms, such as AWS Lambda, Amazon SageMaker, or Amazon Comprehend. Ability to design, iterate, and optimize prompts for various LLM use cases (e.g., summarization, classification, translation, Q&A, and agent workflows). Deep understanding of prompt engineering techniques (zero-shot, few-shot, chain-of-thought, etc.) and their effect on model behavior. Familiarity with prompt evaluation strategies, including manual review, automatic metrics, and A/B testing frameworks. Experience building prompt libraries, reusable templates, and structured prompt workflows for scalable GenAI applications. Ability to debug and refine prompts to improve accuracy, safety, and alignment with business objectives. Awareness of prompt injection risks and experience implementing mitigation strategies. Familiarity with prompt tuning, parameter-efficient fine-tuning (PEFT), and prompt chaining methods. Familiarity with continuous deployment and DevOps tools preferred. Experience with Git preferred Experience working in agile/scrum environments Successful track record interfacing and communicating effectively across cross-functional teams. Good communication, analytical and presentation skills, problem-solving skills and learning attitude

Principle Developer - ML/Prompt Engineer Technologies: Amazon Bedrock, RAG Models, Java, Python, C or C++, AWS Lambda, Responsibilities: Responsible for developing, deploying, and maintaining a Retrieval Augmented Generation (RAG) model in Amazon Bedrock, our cloud-based platform for building and scaling generative AI applications. Design and implement a RAG model that can generate natural language responses, commands, and actions based on user queries and context, using the Anthropic Claude model as the backbone. Integrate the RAG model with Amazon Bedrock, our platform that offers a choice of high-performing foundation models from leading AI companies and Amazon via a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI. Optimize the RAG model for performance, scalability, and reliability, using best practices and robust engineering methodologies. Design, test, and optimize prompts to improve performance, accuracy, and alignment of large language models across diverse use cases. Develop and maintain reusable prompt templates, chains, and libraries to support scalable and consistent GenAI applications. Skills/Qualifications: Experience in programming with at least one software language, such as Java, Python, or C/C++. Experience in working with generative AI tools, models, and frameworks, such as Anthropic, OpenAI, Hugging Face, TensorFlow, PyTorch, or Jupyter. Experience in working with RAG models or similar architectures, such as RAG, Ragna, or Pinecone. Experience in working with Amazon Bedrock or similar platforms, such as AWS Lambda, Amazon SageMaker, or Amazon Comprehend. Ability to design, iterate, and optimize prompts for various LLM use cases (e.g., summarization, classification, translation, Q&A, and agent workflows). Deep understanding of prompt engineering techniques (zero-shot, few-shot, chain-of-thought, etc.) and their effect on model behavior. Familiarity with prompt evaluation strategies, including manual review, automatic metrics, and A/B testing frameworks. Experience building prompt libraries, reusable templates, and structured prompt workflows for scalable GenAI applications. Ability to debug and refine prompts to improve accuracy, safety, and alignment with business objectives. Awareness of prompt injection risks and experience implementing mitigation strategies. Familiarity with prompt tuning, parameter-efficient fine-tuning (PEFT), and prompt chaining methods. Familiarity with continuous deployment and DevOps tools preferred. Experience with Git preferred Experience working in agile/scrum environments Successful track record interfacing and communicating effectively across cross-functional teams. Good communication, analytical and presentation skills, problem-solving skills and learning attitude Mandatory Key Skills Amazon Bedrock,RAG Models,Java,Python,C++,AWS Lambda,RAG model,Anthropic, OpenAI,Hugging Face,TensorFlow,PyTorch,Jupyter,Amazon SageMaker, DevOps tools, Prompt Engineering*