Location - Atlanta GAJob Description We are seeking a highly motivated Conversational AI Engineer to design, develop, and deploy intelligent AI-powered conversational solutions. The ideal candidate will possess strong expertise in Large Language Models (LLMs), Natural Language Processing (NLP), Machine Learning, Generative AI, and Angular-based application development. This role requires hands-on experience building production-ready AI solutions, implementing Retrieval-Augmented Generation (RAG) architectures, and deploying scalable AI applications in cloud environments.
Key Responsibilities- Design, develop, and deploy conversational AI solutions leveraging Large Language Models (LLMs) such as GPT, Llama, and other foundation models.
- Build intelligent chatbots, virtual assistants, and AI-powered applications for enterprise use cases.
- Implement Retrieval-Augmented Generation (RAG) architectures using vector databases and semantic search technologies.
- Develop prompt engineering strategies and optimize prompts to improve response quality, accuracy, and user experience.
- Evaluate, fine-tune, and optimize LLMs for business-specific applications.
- Apply NLP techniques including intent recognition, text classification, sentiment analysis, entity extraction, summarization, and semantic search.
- Utilize frameworks such as TensorFlow, PyTorch, and other AI/ML platforms to build scalable solutions.
- Analyze large datasets and continuously improve model performance through experimentation and optimization.
- Manage the end-to-end lifecycle of AI and machine learning models using MLflow or similar MLOps tools.
- Deploy, monitor, and maintain production-grade AI/GenAI applications.
- Ensure reliability, scalability, and operational excellence of deployed AI solutions.
- Integrate conversational AI capabilities into modern web applications using Angular.
- Develop intuitive and responsive user interfaces for AI-powered experiences.
- Collaborate with backend and AI teams to seamlessly connect LLM and ML services with enterprise applications.
- Implement real-time conversational experiences and intelligent user interactions.
- Validate and review LLM solution architectures to ensure performance, governance, and scalability.
- Deploy AI and machine learning models on cloud platforms such as Azure, AWS, or Google Cloud Platform.
- Stay current with advancements in Generative AI, Conversational AI, LLMs, NLP, and emerging AI technologies.
- Develop proof-of-concepts, prototypes, and pilot solutions to evaluate new technologies.
Required Qualifications- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.
- 5+ years of hands-on experience in AI development, data analysis, and machine learning.
- Proven experience building and deploying production-grade AI/ML solutions.
- Strong expertise in Conversational AI, Generative AI, NLP, and Large Language Models (LLMs).
- Experience with LangChain or similar LLM orchestration frameworks.
- Hands-on experience implementing RAG solutions using vector databases.
- Experience with GPT, Llama, or other commercial/open-source LLMs.
- Strong proficiency in Python and software engineering best practices.
- Experience with Angular and modern web application development.
- Knowledge of MLflow or similar MLOps platforms for model lifecycle management.
- Experience with TensorFlow, PyTorch, or equivalent machine learning frameworks.
- Familiarity with Azure, AWS, or Google Cloud services for AI deployment and scaling.
The base compensation range for this role in the posted location is: $80000 - $90000
Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.
The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.
These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.
It is not typical for candidates to be hired at or near the top of the posted compensation range.
In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.
Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:
- Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
- Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
- Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
- Life and disability insurance
- Employee assistance programs
- Other benefits as provided by local policy and eligibility
Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini's discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.
