Capgemini
Capgemini8 open roles

Forward Deployed Engineer

$85–95kHartford, CTHybridMidFull-time

Posted 2 days ago

The role in short

Lead engagements to design, build, and deploy production-ready agentic AI solutions for insurance clients using Google Cloud technologies.

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.

Location: Hartford, CT (3 days/week from office).

About the Role

Forward Deployed Engineer specializing in AI solution delivery for the insurance industry, responsible for leading engagements from discovery through production deployment. Combines strong insurance domain expertise with deep experience in Google Cloud's AI ecosystem to rapidly design, build, and scale agentic AI solutions that drive measurable business outcomes. Works directly with business and technology stakeholders to translate complex underwriting, claims, pricing, distribution, and servicing challenges into production-ready AI products while contributing reusable accelerators and best practices across engagements.

Required

  • 5+ years of experience with experience in solution engineering, AI engineering, forward-deployed engineering, consulting, or enterprise application development, preferably in client-facing roles.
  • Hands-on experience building GenAI and Agentic AI solutions using Google Cloud technologies such as Vertex AI, Gemini, BigQuery, Agent Builder, Cloud Run, and related services.
  • Strong understanding of LLM application design, prompt engineering, agent orchestration, RAG architectures, evaluation frameworks, and AI governance.
  • Experience designing and integrating enterprise applications, APIs, data platforms, and workflow solutions.
  • Strong business consulting and communication skills with the ability to interact directly with executives, business SMEs, and technical teams.
  • Proven ability to rapidly prototype and iterate solutions, moving from concept to working demonstration within days.
  • Comfortable operating in ambiguous environments with a strong bias toward action, experimentation, and outcome delivery.

Insurance Domain Expertise

  • Strong understanding of Property & Casualty, Life, Reinsurance, or Specialty Insurance operations.
  • Experience supporting business functions such as underwriting, claims, pricing, actuarial, policy administration, customer servicing, distribution, or broker operations.
  • Familiarity with insurance data models, regulatory considerations, document-heavy workflows, and operational processes.
  • Ability to identify AI opportunities that drive measurable business outcomes including loss ratio improvement, underwriting efficiency, claims productivity, customer retention, and agent effectiveness.

Preferred

  • Google Cloud Professional certifications (Generative AI, Machine Learning Engineer, Cloud Architect, or Data Engineer).
  • Experience with insurance platforms such as Guidewire, Duck Creek, Majesco, Sapiens, or similar ecosystems.
  • Exposure to regulated-industry governance, model risk management, auditability, explainability, and AI compliance requirements.
  • Experience developing reusable frameworks, accelerators, and enterprise-scale AI delivery methodologies.

The base compensation range for this role in the posted location is: $85,000 - $95,000

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.

Disclaimers

Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. 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 accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.

Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process.

Click the following link for more information on your rights as an Applicant in the United States. http://www.capgemini.com/resources/equal-employment-opportunity-is-the-law

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.

Prep for this interview

5 questions likely to come up at Capgemini, each matched to a line in this posting.

  1. 1LLMs, RAG and agents
    They wrote: “Strong understanding of LLM application design, prompt engineering, agent orchestration, RAG architectures, evaluation frameworks, and AI governance.”

    A customer wants a chatbot over their internal documents. How do you build it?

    How to answer

    Why they ask: RAG is the most common first project. They want the whole path, from messy files to answers people trust.

    1. Collect and clean the documents; handle permissions per user
    2. Split them into chunks, embed, and store with source links
    3. Retrieve, then answer with citations; say “I don't know” when retrieval is weak
    4. Build a test set of real questions with expected answers before launch

    Tip: Spend more time on the data and on testing than on the model.

  2. 2Discovery and scoping
    They wrote: “Exposure to regulated-industry governance, model risk management, auditability, explainability, and AI compliance requirements.”

    Tell me about a time the customer asked for one thing but needed another.

    How to answer

    Why they ask: Good FDEs spot when a request is a guess at a solution. They want proof you can redirect a customer without losing their trust.

    1. What they asked for, and the detail that made you doubt it
    2. How you tested the doubt (shadowed users, looked at logs, ran a quick prototype)
    3. How you made the case to the customer
    4. What shipped and what changed for them

    Tip: Pick a story where you checked your hunch with data or users before pushing back.

  3. 3Integrations and APIs
    They wrote: “Experience designing and integrating enterprise applications, APIs, data platforms, and workflow solutions.”

    Walk me through connecting our product to a customer's internal system that has no documentation.

    How to answer

    Why they ask: This happens weekly in the job. They want a calm, step-by-step method.

    1. Find who owns the system and get read access to a test environment
    2. Watch real traffic or logs to learn the data shapes
    3. Build a thin adapter with logging around every call
    4. Agree on how failures get reported, and who fixes what

    Tip: Talk about finding the owner of the system first. The code is the easy part.

  4. 4Data and SQL
    They wrote: “Familiarity with insurance data models, regulatory considerations, document-heavy workflows, and operational processes.”

    The customer's data is spread across five systems that disagree. How do you get one clean view?

    How to answer

    Why they ask: Real deployments rarely have one source of truth. They want a practical approach, not a perfect one.

    1. List each system and what it's the best source for
    2. Pick matching keys and decide how to handle records that don't match
    3. Load into one place with clear rules, and keep the raw copies
    4. Show the customer the mismatches; they often fix the source

    Tip: Name the system the business trusts most for each field, and get the customer to agree.

  5. 5Ownership and working with customers
    They wrote: “Comfortable operating in ambiguous environments with a strong bias toward action, experimentation, and outcome delivery.”

    Tell me about a project where the requirements kept changing. What did you do?

    How to answer

    Why they ask: Ambiguity is the norm. They want proof you can keep moving without a clear spec.

    1. The project and why requirements kept moving
    2. What you did to pin them down (short demos, written decisions)
    3. The trade-offs you made to keep shipping
    4. The result, with a number if you have one

    Tip: Show how you reduced the change, beyond how you coped with it.

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