Infosys Limited
Senior Gen AI/Agentic AI Full Stack Lead
Infosys Limited, Charlotte, North Carolina, United States, 28269
Infosys is seeking a hands-on
Gen AI / Agentic AI Lead
to develop and deploy next-generation AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI frameworks. This role is suitable for a mid-level engineer with strong technical skills, a passion for building, and leadership capabilities in a fast-paced environment.
If your skills, experience, and qualifications match those in this job overview, do not delay your application. Key Responsibilities include: Designing, developing, and deploying Gen AI applications with LLMs and agentic frameworks. Fine-tuning open-source and proprietary LLMs using techniques like LoRA, QLoRA, and PEFT. Building and optimizing RAG pipelines with hybrid retrieval and vector search. Integrating Gen AI solutions with cloud-native services such as AWS Bedrock, Azure OpenAI, and GCP Vertex AI. Handling unstructured data and multimodal models. Implementing LLMOps practices including prompt versioning, caching, and observability. Collaborating with cross-functional teams and mentoring junior engineers. Qualifications: Bachelor’s degree in Computer Science, AI/ML, or related field. 5–8 years in software engineering or data science, with 2–3 years in Gen AI or LLM-based systems. Proficiency in Python and ML/AI libraries (Hugging Face Transformers, LangChain, PyTorch). Experience with vector databases (FAISS, Pinecone, Weaviate, Azure AI Search). Familiarity with cloud platforms (AWS, Azure, GCP) and REST API development (FastAPI, Flask). Understanding of AI governance, model safety, and prompt engineering. This position is based in multiple U.S. locations, including Raleigh, NC, Richardson, TX, Tempe, AZ, among others, and may require travel. Estimated annual compensation ranges from $73,000 to $122,275, depending on location. Benefits include health insurance, disability coverage, 401(k), paid holidays, and more. Infosys is committed to equal employment opportunity regardless of race, gender, or background.
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Gen AI / Agentic AI Lead
to develop and deploy next-generation AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI frameworks. This role is suitable for a mid-level engineer with strong technical skills, a passion for building, and leadership capabilities in a fast-paced environment.
If your skills, experience, and qualifications match those in this job overview, do not delay your application. Key Responsibilities include: Designing, developing, and deploying Gen AI applications with LLMs and agentic frameworks. Fine-tuning open-source and proprietary LLMs using techniques like LoRA, QLoRA, and PEFT. Building and optimizing RAG pipelines with hybrid retrieval and vector search. Integrating Gen AI solutions with cloud-native services such as AWS Bedrock, Azure OpenAI, and GCP Vertex AI. Handling unstructured data and multimodal models. Implementing LLMOps practices including prompt versioning, caching, and observability. Collaborating with cross-functional teams and mentoring junior engineers. Qualifications: Bachelor’s degree in Computer Science, AI/ML, or related field. 5–8 years in software engineering or data science, with 2–3 years in Gen AI or LLM-based systems. Proficiency in Python and ML/AI libraries (Hugging Face Transformers, LangChain, PyTorch). Experience with vector databases (FAISS, Pinecone, Weaviate, Azure AI Search). Familiarity with cloud platforms (AWS, Azure, GCP) and REST API development (FastAPI, Flask). Understanding of AI governance, model safety, and prompt engineering. This position is based in multiple U.S. locations, including Raleigh, NC, Richardson, TX, Tempe, AZ, among others, and may require travel. Estimated annual compensation ranges from $73,000 to $122,275, depending on location. Benefits include health insurance, disability coverage, 401(k), paid holidays, and more. Infosys is committed to equal employment opportunity regardless of race, gender, or background.
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