Deployment Associate, Fast Forward Program

About Moder

Moder is an AI-enabled, human-powered digital services company built for mortgage, insurance, and financial services. Moder partners with Palantir to bring Foundry and AIP to clients, enabling the transition from AI experimentation to operational reality.

The Opportunity: Deployment Associate, Fast Forward Program

This is a full-time, structured launchpad for recent graduates interested in building a career in AI deployment. Associates in this program will be the first to experience "Foundry Academy," deploy on live client engagements, and provide feedback that will shape future training and development for FDEs. The program is designed for technically sharp engineers curious about real-world AI deployment within financial institutions, focusing on messy data, legacy systems, and high stakes. Associates are expected to be active contributors from week one, working on real problems alongside experienced engineers.

What Makes This Different

• You Build the Playbook: Cohort 1 will help create the program's onboarding, training curriculum, and deployment methodology.
• Hybrid in Philadelphia: At least three days per week in Moder's Philadelphia hub for in-person learning and collaboration. Periodic travel to client sites is also required.
• Technical and Human Skills: Develops both technical depth (data pipelines, AI workflows) and communication clarity for diverse audiences.
• Designed Career Path: The Fast Forward Program is the entry point to the FDE track: Associate FDE → FDE → Senior FDE → Principal FDE. Advancement is based on delivery, not tenure.
• Inquisitive and Rewarded: Curiosity is a job requirement, with active space created for exploration and questioning.

Key Responsibilities

Technical Delivery & Platform Engineering

• Work on active Palantir Foundry deployments with senior FDEs, owning defined scopes on real client engagements.
• Build data pipelines, ontology structures, and workflow automations in Foundry's Pipeline Builder and Workshop.
• Wrangle and transform complex financial services datasets for use within Palantir's ontology layer.
• Develop proficiency in Foundry's core tools: Pipeline Builder, Workshop, Ontology Manager, Code Repositories, and AIP.
• Contribute to architecture and technical design discussions.
• Build familiarity with AI and LLM-driven workflows through Palantir AIP.

Client Engagement & Collaboration

• Participate in client-facing sessions (discovery meetings, technical reviews, status updates).
• Support training and handoff sessions for client teams.
• Translate technical realities into business language for various audiences.
• Represent Moder at client locations when travel is required.

Program Development & Field Intelligence

• Actively participate in Moder Academy, providing feedback on the onboarding program covering the mortgage lifecycle, insurance operations, Palantir Foundry, and client engagement frameworks.
• Maintain a structured learning log to feed insights back to Moder's product and training teams.
• Complete a capstone project (client-facing workflow or internal accelerator) and present it to Moder leadership.
• Provide formal feedback at structured checkpoints to improve the program.

Qualifications

Required

• Recent graduate (undergraduate or graduate) with a degree in Computer Science, Data Science, Software Engineering, Information Systems, Mathematics, or a related technical field.
• Programming ability in Python for data manipulation, API calls, and scripting.
• Working SQL proficiency for querying and exploring datasets.
• Highly analytical mindset with the ability to break down problems and build structured cases.
• High degree of intellectual curiosity and inquisitiveness.
• Clear written and verbal communication skills, to both technical and non-technical audiences.
• Comfort with ambiguity and open-ended environments.
• Ability to commute to and work from Philadelphia at least three days per week.

Preferred

• Coursework, projects, or research involving data engineering, machine learning, enterprise data platforms, or applied AI.
• Exposure to AI/ML concepts including LLMs, retrieval-augmented generation, or agentic systems.
• Prior experience in a client-facing, consulting, or applied research capacity.
• Background or coursework in financial services, mortgage, insurance, or a regulated industry.
• Familiarity with cloud environments (AWS, Azure, or GCP).