Gen AI/ ML Engineer (RAG & Agentic AI)

Position Title : Gen AI / ML Engineer (RAG & Agentic AI) Location : New York City, NY / Charlotte, NC (Hybrid/Onsite) Experience : 8+ Years Preferred Employee Type : Full Time with Benefits Note :- In Person Interview Job Description: We are seeking a highly skilled GenAI / ML Engineer with hands-on experience in Retrieval-Augmented Generation (RAG) and Agentic AI systems to design, develop, and deploy next-generation AI solutions. The ideal candidate will have strong expertise in building intelligent systems using LLMs, orchestration frameworks, and scalable ML pipelines. Key Responsibilities Design and implement GenAI solutions using Large Language Models (LLMs) such as GPT, Claude, or open-source models Build and optimize RAG pipelines leveraging vector databases (e.g., Pinecone, FAISS, Weaviate, Chroma) Develop Agentic AI systems capable of planning, reasoning, and multi-step task execution using frameworks like LangChain, LlamaIndex, Semantic Kernel, or similar Integrate LLMs with enterprise data sources, APIs, and tools for real-world use cases Fine-tune, evaluate, and monitor model performance for accuracy, latency, and cost efficiency Develop scalable and production-ready ML pipelines using cloud platforms (Azure, AWS, or GCP) Collaborate with cross-functional teams to translate business requirements into AI-driven solutions Implement best practices for prompt engineering, guardrails, and responsible AI Stay updated with latest advancements in GenAI, LLMOps, and agent-based architectures Required Skills & Qualifications Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related field 5+ years of experience in Machine Learning / AI development Strong programming skills in Python Hands-on experience with LLMs and GenAI frameworks Proven experience in building RAG-based applications Experience with Agentic AI / autonomous agents / multi-agent systems Familiarity with vector databases and embeddings Experience with ML frameworks such as PyTorch, TensorFlow, or Hugging Face Exposure to API integrations, microservices architecture, and RESTful services Experience working with cloud platforms (AWS / Azure / GCP) Preferred Qualifications Experience with LLMOps tools and model deployment frameworks Knowledge of fine-tuning techniques (LoRA, PEFT, RLHF) Experience in knowledge graph integration Familiarity with CI/CD pipelines and containerization (Docker, Kubernetes) Prior experience in enterprise AI implementations Key Competencies Strong problem-solving and analytical skills Excellent communication and collaboration abilities Ability to work in a fast-paced and innovation-driven environment If your Interested, Kindly, share us your resume on abuzar.umar@capgemini.com Life At Capgemini Capgemini supports all aspects of your well-being throughout the changing stages of your life and career. For eligible employees, we offer: Flexible work Healthcare including dental, vision, mental health, and well-being programs Financial well-being programs such as 401(k) and Employee Share Ownership Plan Paid time off and paid holidays Paid parental leave Family building benefits like adoption assistance, surrogacy, and cryopreservation Social well-being benefits like subsidized back-up child/elder care and tutoring Mentoring, coaching and learning programs Employee Resource Groups Disaster Relief Disclaimer Capgemini is an Equal Opportunity Employer encouraging diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law. This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodations do not pose an undue hardship. Capgemini is committed to providing reasonable accommodations during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact. Click the following link for more information on your rights as an Applicant http://www.capgemini.com/resources/equal-employment-opportunity-is-the-law Show more Show less