Forward Deployed Engineer - AI
Posted 4 days ago
The role in short
Embed with business teams to rapidly design, build, and validate production AI applications, agents, and integrations, transitioning mature solutions to delivery teams.
FCCI is guided by our core values of Loyalty, Integrity, Vision, Excellence and Service. These are the principles and behaviors that guide how we support and trust one another, build our teams, cultivate leaders and create a company that feels like family. If these are your values, we’d like you to join our team.
This key role will be responsible for accelerating the delivery of high-value AI solutions across the enterprise. The FDE will work directly with business, architecture, data, security, and delivery teams to understand complex problems, rapidly build AI-enabled solutions, and help move successful concepts into production.
The key responsibilities will be:
- Working directly with business teams to identify and define high-value AI opportunities.
- Rapidly design, build, test and validate AI applications, agents, copilots and workflow solutions.
- Integrate AI capabilities with enterprise applications, APIs, data platforms and knowledge repositories.
- Apply techniques such as RAG, agentic workflows, tool calling, prompt/context engineering and AI evaluation.
- Partner with Architecture, Security, Data, Risk and Compliance teams to ensure solutions meet enterprise standards.
- Establish evaluation, monitoring, and reliability approaches for AI solutions.
- Operate from problem discovery through technical validation and early productionization, then transition ongoing ownership to the appropriate delivery team.
- Convert successful implementations into reusable components, patterns, and reference implementations.
- Transition mature solutions, documentation, and knowledge to delivery teams for ongoing ownership, support and enhancement.
In exchange for your talents, FCCI offers competitive salaries and an excellent benefits package which includes:
- Flexible Work Environment
- Paid Family Leave
- Competitive PTO & Holidays
- Recognition & Bonus Programs
- Medical, Vision, Dental & Life Insurance
- Employee Referral Bonus
- Paid Volunteer Time
- 401(k) Match & Profit-Sharing
The salary range for this position is $118,864-$183,051 annually. This salary range is an estimate and the actual salary will vary based on applicant’s education, experience, knowledge, skills, and abilities.
We are an Equal Employment Opportunity employer. Applicants and employees are considered for positions and are evaluated without regard to mental or physical disability, race, color, religion, gender, national origin, age, genetic information, military or veteran status, sexual orientation, marital status or any other protected Federal, State/Province or Local status unrelated to the performance of the work involved.
Please apply via our website at www.fcci-group.com.
Drug Free Workplace (*Pre-employment drug screen is conducted for all positions)
Qualifications
Required
- Bachelor's Degree in Computer Science, IT, or Information Systems (Note: Relevant, progressively responsible work experience may be substituted on a year-for-year basis for the required education.)
- Minimum of four years of software engineering, application development, or technical solution delivery experience
- Strong hands-on programming skills in Python and/or JavaScript/TypeScript.
- Experience building production applications and APIs.
- Hands-on experience with large language models and generative AI.
- Experience with cloud platforms, enterprise integration, and modern AI techniques such as RAG agents, vector search, and evaluation.
- Strong problem-solving and communication skills, with the ability to work across business and technical teams.
- Experience in a regulated enterprise environment.
- Experience with P&C/commercial insurance processes, such as underwriting, policy servicing, claims, billing, payments, or agent/customer servicing.
- Experience with platforms such as AWS Bedrock, Azure AI, OpenAI, Anthropic, Databricks, or similar technologies.
- Ability to understand and improve systems; evaluates system’s current state/practices and recommend modifications.
- Ability to analyze, define and solve problems; the use of good judgment and decision-making.
Preferred
- AWS AI Practitioner, AWS Machine Learning Engineer, AWS Solutions Architect Associate, Azure AI Engineer Associate, or other relevant Databricks/AI/Data/AWS certifications
Licenses & Certifications
Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws.
For further information, please review the Know Your Rights notice from the Department of Labor.
Prep for this interview
5 questions likely to come up at FCCI Insurance Group, each matched to a line in this posting.
- 1LLMs, RAG and agents
They wrote: “Apply techniques such as RAG, agentic workflows, tool calling, prompt/context engineering and AI evaluation.”
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.
- Collect and clean the documents; handle permissions per user
- Split them into chunks, embed, and store with source links
- Retrieve, then answer with citations; say “I don't know” when retrieval is weak
- 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.
- 2Cloud, deployment and security
They wrote: “Partner with Architecture, Security, Data, Risk and Compliance teams to ensure solutions meet enterprise standards.”
The customer's security team sends a 200-question review. How do you handle it?
How to answer
Why they ask: Security reviews often block deals. FDEs help get through them.
- Start from your company's standard answers (SOC 2 report, past reviews)
- Answer clearly; don't oversell
- Bring in your security team for anything you're unsure of
- Keep the new answers for the next customer
Tip: Reuse past answers, flag honest gaps, and offer a call for the hard questions.
- 3Coding
They wrote: “Strong hands-on programming skills in Python and/or JavaScript/TypeScript.”
Here's a CSV export from a customer. Write a script that cleans it and loads it into our API.
How to answer
Why they ask: Very close to real FDE work. They watch how you handle bad rows and failures.
- Read with a proper CSV parser; check the header first
- Validate each row and collect errors, not crash on the first one
- Send in batches with retries and a clear report at the end
- Write one or two quick tests for the parsing
Tip: Talk through edge cases out loud: encodings, missing fields, duplicates, rate limits.
- 4Discovery and scoping
They wrote: “Operate from problem discovery through technical validation and early productionization, then transition ongoing ownership to the appropriate delivery team.”
A customer says “we want AI in our claims process.” What do you ask in the first meeting?
How to answer
Why they ask: Most FDE work starts this vague. They want to hear you find the real problem before you pick a tool.
- Map the current process: who touches a claim, in what order, with which systems
- Find the slowest or most error-prone step and ask what it costs them
- Agree on one measurable goal (for example time per claim, or error rate)
- Ask what data you can access, and who signs off on security
Tip: Ask about the work, not the technology. Who does it today, how long it takes, what a mistake costs, and how they'd know it got better.
- 5Integrations and APIs
They wrote: “Integrate AI capabilities with enterprise applications, APIs, data platforms and knowledge repositories.”
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.
- Find who owns the system and get read access to a test environment
- Watch real traffic or logs to learn the data shapes
- Build a thin adapter with logging around every call
- 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.
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