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About the role
Please share profiles for the below JD. We need to fill the positions soon. Job Description: Responsibilities: · Design and Develop AI/ML solutions using enterprise approved tools/technologies. · Develop reusable AI capabilities (“skills”) such as copilots, agents, APIs, and domain-specific automation components for enterprise use. · Build and operationalize AI-powered skills including coding assistants, recommendation engines, search assistants, and workflow automation tools. · Develop and implement efficient Retrieval-Augmented Generation (RAG) model-based generative AI solutions, including text-to-code, diagram-to-code, text-to-recommendations, and diagram-to-recommendations services. · Implement AI-based searches, chatbots, and APIs to enhance user experience and functionality. · Design and develop generative AI, Open API, Large Language Models (LLM), RAG, or AI agent-based implementations. · Utilize vector databases and indexing techniques to optimize AI solutions. · Work in cloud environments such as Azure (preferred) or AWS (acceptable) to deploy and manage AI solutions. · Experience designing or implementing agent-based AI systems, including: o Tool invocation and function calling o Multi-step decision and reasoning chains o Autonomous task execution and completion · Familiarity with agent orchestration frameworks or patterns like LangGraph, AutoGen or Crew AI. Qualifications: · Proven experience in designing and developing AI “skills” (modular AI components such as copilots, agents, plugins, APIs, or reusable services). · Define and implement metrics for evaluation (e.g., using Ragas/DeepEval) to measure the reliability, accuracy, and memory retention of agentic systems in production · Proficiency in designing and developing generative AI, Open API, LLM, RAG, or AI agent-based implementations. · Experience with vector databases and indexing techniques. · Experience in developing and implementing MCP server for integration with AI agents like Copilot in agent mode etc. · Strong programming skills in one or more leading programming languages such as .NET, Python, NodeJS. · Experience working in cloud environments, particularly Azure (preferred) or AWS (acceptable). · Experience with fine-tuning models (LoRA/QLoRA) to enhance agent behavior. Preferred Qualifications: · Experience building enterprise-grade AI skill catalogs, developer platforms, or reusable AI frameworks is a strong plus. · Experience building reusable Terraform frameworks or internal developer platforms for AI workloads. · Experience standardizing IaC templates across teams (platform engineering mindset). · Advanced degree in Computer Science, Engineering, or a related field. · Experience in cloud platforms and Terraform Infrastructure as Code. · Strong adherence to secure code practices. · Monitoring, logging, and alerting for production systems using Splunk.
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