Capgemini Invent - AI Solutions Architecture...

Capgemini
Chicago, IL, United States
2 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Compensation
$105,600.0 - $199,480.0
Working hours
Regular working hours
Job source

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Machine Learning Delivery Pipeline Large Language Models Data Layers Kubernetes

Job description

At Capgemini Invent, we believe difference drives change. As inventive transformation consultants, we blend our strategic, creative and scientific capabilities, collaborating closely with clients to deliver cutting-edge solutions. Join us to drive transformation tailored to our client’s challenges of today and tomorrow. Informed and validated by science and data. Superpowered by creativity and design. All underpinned by technology created with purpose.

About the Job You’re Considering

At Capgemini Invent, our Data Driven Transformation (DDT) team makes AI work at scale by combining data science and engineering with business consulting. We build context-driven analytics and GenAI/agentic systems that reflect how decisions and work actually happen-grounded in semantic layers, strong data foundations, and governance embedded in decision flows. With a builder-advisor (“forward deployed”) mindset, DDT delivers production-ready impact across operations and customer domains, redefining what enterprise AI advisory looks like in practice.

Your Role

As an AI Solutions & Engineering Senior Consultant, you will own defined technical workstreams and deliver end-to-end AI solution components within an established architecture. You will make independent technical decisions, engage directly with client engineering teams, and help ensure AI solutions are robust, governed, and ready for production use.

You will:

  • Design and implement end-to-end AI solution components within a defined architecture

  • Build governed agentic workflows, inference pipelines, and API layers

  • Make independent technical decisions and explain them to client engineers

Requirements

You bring strong AI literacy, including core AI and generative AI concepts, and understand how these capabilities apply to enterprise transformation. You are able to identify and support AI-enabled opportunities that improve business outcomes and delivery effectiveness, and you have experience working in AI-augmented ways of working to enhance research, analysis, and solution development. You collaborate effectively across strategy, technology, data, and design to enable AI-driven solutions, with a solid understanding of responsible AI principles such as ethics, privacy, security, and governance. You demonstrate curiosity and a continuous learning mindset around emerging AI capabilities and their practical application in client environments., + 5-6 years in software or AI/ML engineering

  • Strong hands-on experience with LLM systems (RAG, function calling, agents)

  • Experience with orchestration frameworks and vector databases

  • Solid cloud deployment, monitoring, and security knowledge

  • Ability to operate independently on client workstreams

Benefits & conditions

The base compensation range for this role in the posted location is: $105,600 - $199,480.

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)

About the company

Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on juju.com

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

4:52 min

Delivering diverse consulting services from agile to artificial intelligence

Ranjit Lopez Ranjit Lopez · Europe 2026 Virtual

2:28 min

Understanding Kubernetes architecture and core cluster components

Marc Nimmerrichter · WWC 2022

1:58 min

Shifting security permissions from applications to the data layer

Neena Thomas Neena Thomas · WWC Europe 2026

2:36 min

Applying supervised machine learning for practical rule extraction

Katja Träumner

52 sec

Transitioning from software consulting to AI building

Malte Lensch Malte Lensch · WWC Europe 2026

4:04 min

Overview of Kubernetes operators and custom resource definitions

Philipp Krenn · WWC 2022

Videos

See all

Related articles

See all