Senior Palantir Forward Deployed Engineer - GPS
Posted 7 days ago
The role in short
Embed with government clients to prototype and deliver production-grade GenAI solutions using Palantir Foundry/AIP.
Position Summary
Our Deloitte AI & Engineering team works to transform technology platforms, drive innovation, and help make a significant impact on our clients’ success. You’ll work alongside talented professionals reimagining and reengineering operations and processes that are critical to businesses. Your contributions can help clients improve financial performance, accelerate new digital ventures, and fuel growth through innovation.
Work you'll do
As a Senior Palantir FDE, you will work side by side with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This requires a highly motivated practitioner who moves with speed and precision, building working software, engaging confidently with senior stakeholders and engineers to bring measurable business impact from day one. Additional responsibilities include:
Client Engagement
- Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.
- Partner with leaders, product owners, architects, and engineers to align priorities and delivery.
- Lead working sessions to shape solutions and drive client outcomes.
- Prototype and deliver working AI solutions using industry expertise and emerging capabilities.
- Contribute independently within an FDE pod while mentoring newer team members.
- Coach client teams and end users on platform capabilities and AI enablement, while building trusted relationships, managing expectations, and supporting long-term engagement success.
- Drive end-to-end sales and delivery support by developing demos/POCs, contributing to proposals and orals, articulating business value, and documenting solutions for smooth client handoff and knowledge transfer.
- Strengthen team and organizational impact by mentoring other FDEs through design/code reviews and feedback, while contributing reusable components to intellectual capital.
Solution Engineering
- Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.
- Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.
- Apply architecture decisions that balance quality, safety, latency, cost, and model risk.
- Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.
- Design extensible functionality, support sprint sizing, and align solutions with senior team members.
- Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.
A successful candidate would possess these skills:
- Ability to work independently and collaborate as part of a team
- Effective written and verbal communication skills
- Meticulous attention to detail and quality of work product
- Ability to build and sustain professional relationships
- Ability to lead projects or workstreams
- Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
- Strong interpersonal skills and professional demeanor
- Ability to meet deadlines
- Ability to mentor and provide clear guidance to others
The team
Deloitte’s Government & Public Services (GPS) practice – our people, ideas, technology and outcomes – is designed for impact. Serving federal, state, & local government clients as well as public higher education institutions, our team of professionals brings fresh perspective to help clients anticipate disruption, reimagine the possible, and fulfill their mission promise.
Our AI & Data offering provides a full spectrum of solutions for designing, developing, and operating cutting-edge Data and AI platforms, products, insights, and services. Our offerings help clients innovate, enhance, and operate their data, AI, and analytics capabilities, ensuring they can mature and scale effectively with organizational intelligence programs and differentiated strategies to win in their chosen markets.
Qualifications
Required:
- Bachelor's degree (or equivalent) in Computer Science, Data Science, or Engineering.
- 7+ years of experience in software engineering, data engineering, data science, or analytics engineering.
- 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments.
- 1+ years of experience with Palantir, including hands-on experience with one of the following key platform technologies: Foundry, AIP, Maven.
- 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions.
- 1+ years of experience building reliable, maintainable, and well-documented code.
- Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.
- Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.
- Ability to obtain and maintain a US government security clearance.
Preferred:
- Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking).
- Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments.
- Data engineering experience with Spark, Airflow/dbt, streaming, data modeling, or ML/data science background feature engineering, experimentation, or model evaluation.
- Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management.
- Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures.
- Experience operating within hybrid onshore/offshore teams.
- Familiarity with security, privacy, and compliance considerations.
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $155,600 to $306,800.
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.
ai&e fy27 profile
Deloitte is committed to providing reasonable accommodations for people with disabilities. If you require a reasonable accommodation to participate in the recruiting process, please direct your inquiries to the Global Call Center (GCC) at USTalentCICInbox@deloitte.com.
Recruiting tips
From developing a stand out resume to putting your best foot forward in the interview, we want you to feel prepared and confident as you explore opportunities at Deloitte. Check out recruiting tips from Deloitte recruiters.
Benefits
At Deloitte, we know that great people make a great organization. We value our people and offer employees a broad range of benefits. Learn more about what working at Deloitte can mean for you.
Our people and culture
Our inclusive culture empowers our people to be who they are, contribute their unique perspectives, and make a difference individually and collectively. It enables us to leverage different ways of thinking, ideas, and perspectives, and bring more creativity and innovation to help solve our clients' most complex challenges. This makes Deloitte one of the most rewarding places to work.
Our purpose
Deloitte’s purpose is to make an impact that matters for our people, clients, and communities. At Deloitte, purpose is synonymous with how we work every day. It defines who we are. Our purpose comes through in our work with clients that enables impact and value in their organizations, as well as through our own investments, commitments, and actions across areas that help drive positive outcomes for our communities. Learn more.
Professional development
From entry-level employees to senior leaders, we believe there’s always room to learn. We offer opportunities to build new skills, take on leadership opportunities and connect and grow through mentorship. From on-the-job learning experiences to formal development programs, our professionals have a variety of opportunities to continue to grow throughout their career.
As used in this posting, "Deloitte" means Deloitte Consulting LLP, a subsidiary of Deloitte LLP. Please see https://www.deloitte.com/us/about for a detailed description of the legal structure of Deloitte LLP and its subsidiaries.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or protected veteran status, or any other legally protected basis, in accordance with applicable law.
Prep for this interview
5 questions likely to come up at Deloitte, each matched to a line in this posting.
- 1Cloud, deployment and security
They wrote: “Ability to obtain and maintain a US government security clearance.”
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.
- 2Discovery and scoping
They wrote: “Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.”
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.
- 3Integrations and APIs
They wrote: “Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures.”
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.
- 4Data and SQL
They wrote: “Data engineering experience with Spark, Airflow/dbt, streaming, data modeling, or ML/data science background feature engineering, experimentation, or model evaluation.”
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.
- List each system and what it's the best source for
- Pick matching keys and decide how to handle records that don't match
- Load into one place with clear rules, and keep the raw copies
- 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.
- 5LLMs, RAG and agents
They wrote: “Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.”
When would you use an agent that takes actions, and how do you keep it safe?
How to answer
Why they ask: Agent work is growing fast in FDE postings. Senior candidates are expected to know where agents fail.
- Use agents for multi-step tasks with clear success checks; avoid them where one wrong action is costly
- Give the agent narrow tools and permissions, not broad access
- Require human approval for risky actions
- Log every step so the customer can audit it
Tip: Start from the cost of a wrong action. Limit what the agent can do, and log everything.
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