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Confirmed on the employer's own hiring board on Nov 9, 2026. First seen by Alion on Nov 6, 2026. IBM scores A on the Alion truth index.

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IBM

IBM is an American technology company whose roots go back to the 1911 formation of the Computing-Tabulating-Recording Company, and which has been headquartered in Armonk, New York for decades. It defined mainframe computing, the personal computer standard and much of enterprise data processing, and today concentrates on hybrid cloud built around Red Hat, enterprise AI through the watsonx platform, consulting services and the mainframe and storage systems that still run the world's largest transaction workloads. The company also runs one of the leading quantum computing programmes and consistently ranks among the largest recipients of United States patents.

A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You'll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you'll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You'll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences. As a Technical Consultant specializing in AI Integration, you will implement, configure, and customize AI-driven solutions that integrate seamlessly into enterprise applications and workflows. This role requires translating solution designs and architectural blueprints into working systems, ensuring secure, efficient, and compliant deployment of AI services, APIs, and orchestration layers. Your primary responsibilities will include:

  • Implement AI Solutions: Develop connectors, build Retrieval-Augmented Generation (RAG) pipelines, and configure prompts and guardrails to integrate AI services into enterprise applications and workflows.
  • Collaborate with Stakeholders: Work closely with architects, data engineers, and business stakeholders to validate requirements, deliver proofs of concept, and harden solutions for production.
  • Optimize Performance: Implement observability, performance tuning, and cost optimization measures to ensure reliable and scalable AI solutions.
  • Ensure Compliance: Deploy AI services, APIs, and orchestration layers in compliance with organizational and regulatory standards.
  • Deliver Solutions: Translate solution designs and architectural blueprints into working systems, focusing on reliability, scalability, and responsible AI principles throughout the delivery lifecycle.
  • Exposure to API Integration: Hands-on experience with integrating AI services and APIs into enterprise applications and workflows, including developing connectors and configuring prompts and guardrails.
  • Experience with Workflow Automation: Familiarity with workflow automation and event-driven patterns, including building Retrieval-Augmented Generation (RAG) pipelines and implementing orchestration layers.
  • LLMOps Practices: Exposure to LLMOps practices, including implementing observability, performance tuning, and cost optimization measures to ensure reliable and scalable AI solutions.
  • Secure Deployment: Experience with deploying AI services, APIs, and orchestration layers in compliance with organizational and regulatory standards, ensuring secure and efficient deployment.
  • AI Solution Development: Experience working with AI solution designs and architectural blueprints, translating them into working systems that integrate seamlessly into enterprise applications and workflows.
  • Workflow Automation Expertise: Familiarity with workflow automation and event-driven patterns, including building Retrieval-Augmented Generation (RAG) pipelines and implementing orchestration layers, is beneficial for this role.
  • LLMOps Practices Knowledge: Exposure to LLMOps practices, including implementing observability, performance tuning, and cost optimization measures, is advantageous for ensuring reliable and scalable AI solutions.
  • Secure Deployment Experience: Experience with deploying AI services, APIs, and orchestration layers in compliance with organizational and regulatory standards is desirable, ensuring secure and efficient deployment. India Project Management Hybrid Professional Hyderabad, IN Hyderabad (0063) IBM India Private Limited Artificial Intelligence Integration Optimization Performance Tuning Delivery Pipelines Enterprise Applications Observability Compliance Application Programming Interface Workflow Automation Musical Orchestration Large Language Model Operations
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