AI Solutions Developer

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.

Job Description We are seeking a highly skilled AI Solutions Developer with strong expertise in building end to end AI/ML applications using Python and modern AI frameworks such as LangChain PyTorch and TensorFlow. The role involves designing developing and deploying intelligent solutions including LLM powered applications machine learning models automation pipelines and AI driven integrations

Responsibilities

• AI/ML Model Development: Design build and optimize machine learning and deep learning models using PyTorch TensorFlow and related frameworks
• LLM Generative AI Solutions: Develop applications powered by Large Language Models using LangChain vector databases embeddings and prompt orchestration frameworks
• Python Based Application Development: Build scalable AI services automation tools and backend components using Python
• Data Engineering Pipelines: Prepare transform and manage datasets build feature pipelines and model training workflows
• Model Deployment MLOps: Deploy models into production using APIs containerization Docker CICD and cloud platforms
• Evaluation Optimization: Perform model tuning evaluation and performance optimization to ensure accuracy efficiency and reliability
• Cross Functional Collaboration: Work closely with product engineering and business teams to translate strategic requirements into AI driven technical solutions
• Experimentation Research: Stay up to date with emerging AI technologies evaluate new tools and prototype innovative solutions

Required Skills

• Strong hands on experience with Python for AI/ML development
• Proficiency with PyTorch TensorFlow or similar deep learning frameworks
• Experience developing LLM based applications using LangChain embeddings vector databases FAISS Chroma Pinecone or similar technologies
• Ability to design and implement end to end ML pipelines training validation deployment
• Strong understanding of machine learning concepts NLP and deep learning architectures
• Solid experience with APIs microservices and cloud based deployment
• Strong analytical debugging and problem solving skills

The base compensation range for this role in the posted location is: 56,186 - 87,556

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.

Benefits 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 oth…