Job Description
The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.
Company Overview
A leading global professional services organization is seeking a Forward Deployed Engineer – Palantir to help organizations accelerate enterprise AI adoption by delivering innovative, scalable, and production-ready AI solutions. This role combines software engineering, AI development, and client engagement to solve complex business challenges through modern AI platforms, cloud technologies, and enterprise-scale engineering practices.
The organization is seeking a Forward Deployed Engineer – Palantir to work closely with client stakeholders, technical teams, and engineering leaders to rapidly prototype and deploy high-impact Generative AI solutions. The role requires a hands-on engineer who excels at building production-ready software, collaborating with cross-functional teams, and translating business challenges into scalable AI-driven solutions.
The successful candidate will contribute to enterprise AI transformations by developing agentic workflows, designing scalable AI architectures, and implementing engineering best practices that deliver measurable business value. This position also offers the opportunity to mentor junior engineers while working in a collaborative, pod-based delivery model.
Key Responsibilities
- Partner directly with clients to understand business objectives and translate high-value AI use cases into practical solutions.
- Collaborate with business leaders, product owners, architects, and engineering teams to align project priorities and delivery plans.
- Lead workshops and solution design sessions to define AI strategies and drive successful project outcomes.
- Prototype, develop, and deploy enterprise-grade Generative AI solutions using modern AI technologies.
- Contribute independently within engineering delivery teams while mentoring junior engineers.
- Build AI-powered applications, agentic platforms, and intelligent workflows across enterprise AI ecosystems.
- Develop scalable AI engineering patterns, reusable frameworks, and human-in-the-loop processes.
- Make architectural decisions that balance quality, performance, security, cost, and model reliability.
- Deliver production-quality software using industry best practices, including testing, CI/CD, logging, documentation, and version control.
- Design extensible platform capabilities and contribute reusable assets such as code libraries, prompt templates, runbooks, and reference implementations.
- Support sprint planning, solution estimation, and collaboration across distributed engineering teams.
Required Qualifications
- Bachelor’s degree or equivalent in Computer Science, Data Science, Engineering, or a related discipline.
- 3+ years of experience in software engineering, data engineering, data science, or analytics engineering.
- 1+ year of hands-on experience building and deploying Generative AI or Large Language Model (LLM) solutions in production or client environments.
- 1+ year of hands-on experience with Palantir platforms, including Foundry, AIP, Maven, or related technologies.
- Experience leading project workstreams and translating business requirements into AI-driven solutions.
- Experience developing reliable, maintainable, and well-documented software.
- Willingness to travel up to 50% based on project and client requirements.
- Strong communication, collaboration, and stakeholder management skills.
Preferred Qualifications
- Experience working with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.
- Experience collaborating directly with client engineering teams in fast-paced delivery environments.
- Knowledge of data engineering technologies such as Apache Spark, Airflow, dbt, streaming platforms, or data modeling.
- Experience with machine learning, feature engineering, experimentation, or model evaluation.
- Familiarity with MLOps or LLMOps practices, including model monitoring, evaluation frameworks, and prompt management.
- Experience integrating LLM solutions with enterprise applications using APIs, microservices, or event-driven architectures.
- Experience working within hybrid onshore and offshore engineering teams.
- Understanding of enterprise security, privacy, and regulatory compliance best practices.
Disclaimer
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