Forward Deployed Engineer

We are seeking Senior/Principal Forward Deployed Engineers (FDEs) to work directly with strategic enterprise customers and architect, build, and deploy high-impact AI, Data, and GenAI solutions.About the RoleThis role is designed for a highly hands-on Palantir Echo-style profile—someone who can operate at the intersection of software engineering, data engineering, AI/ML, solution architecture, and customer engagement. The ideal candidate will be comfortable going beyond advisory work to personally design, build, deploy, and optimize production solutions while working directly with customers and senior stakeholders. You will own solutions end-to-end, from understanding ambiguous business problems and rapidly prototyping solutions through production deployment, optimization, and knowledge transfer.ResponsibilitiesDiagnose critical business challenges, understand customer requirements, and map enterprise data landscapes.Co-design and deliver AI solutions directly with customers.Own the full solution lifecycle, including discovery, architecture, prototyping, development, deployment, and post-production optimization.Design and implement agentic AI workflows, RAG pipelines, knowledge graphs, and real-time decision-making applications.Build rapid prototypes and POCs that demonstrate measurable business value within days or weeks.Architect production-grade Enterprise AI solutions using Palantir Foundry/AIP, Partner Foundry Solutions, Rackspace Private Cloud, and GPU infrastructure.Integrate AI applications with enterprise platforms including ERP, CRM, data warehouses, data lakes, and streaming systems.Develop scalable data pipelines for structured and unstructured data using ETL/ELT technologies.Implement solutions using vector databases such as Pinecone, Weaviate, and AstraDB.Develop and fine-tune LLM/SLM solutions and implement RAG architectures using frameworks such as LlamaIndex and Haystack.Build and orchestrate multi-agent workflows using technologies such as LangChain, LangGraph, and CrewAI.Contribute across the full technology stack, including Python, Node.js/Go, React/Vue, SQL/NoSQL, Docker, Kubernetes, and CI/CD.Implement observability, monitoring, telemetry, versioning, and governance for production AI systems.Identify additional AI opportunities within customer environments and work with Sales and Customer Success teams to expand engagements.Provide structured feedback to Platform Engineering and Product teams based on customer requirements and field experience.Develop reusable reference architectures, accelerators, frameworks, and engineering best practices.Mentor engineers and customer teams and support knowledge transfer.QualificationsPalantir certification is mandatory.Strong hands-on experience with Palantir Foundry; experience with Palantir AIP and Ontology is highly preferred.6+ years of experience in software engineering, data engineering, AI/ML, or related technical delivery.4+ years of customer-facing, consulting, field engineering, solutions engineering, or FDE experience.Proven experience building and deploying production-grade AI/ML solutions at enterprise scale.Strong proficiency in Python.Experience with Node.js or Go and modern frontend technologies such as React or Vue.Strong SQL/NoSQL database experience.Hands-on experience with: LLMs and prompt engineeringRAG architecturesVector databasesData pipelinesAI/ML applicationsAgent orchestrationApplication dashboardsKnowledge graphsSemantic/ontology-based modelingStrong DevOps and cloud-native experience, including Docker, Kubernetes, CI/CD, and production deployment.Experience integrating heterogeneous enterprise data and application systems.Ability to translate ambiguous business requirements into actionable technical and engineering plans.Excellent verbal and written communication skills.Comfortable conducting technical workshops, customer presentations, and C-suite engagements.Preferred SkillsExperience with Palantir Foundry, AIP, and Ontology modeling.Experience with Enterprise AI platforms such as Uniphore BAIC or similar technologies.Experience with SLM fine-tuning, model distillation, RLHF, and AI evaluation frameworks.Strong experience building agentic AI and multi-agent systems, including tool use and autonomous workflow orchestration.Familiarity with GPU infrastructure, including NVIDIA H100/B200 and InfiniBand.Experience with private cloud technologies such as OpenStack or VMware.Background in technology consulting, AI startups, Forward Deployed Engineering, or Solutions Engineering Experience in one or more of the following industries: Financial ServicesHealthcareSupply ChainDefenseEnergyManufacturingExperience with knowledge graphs, semantic modeling, and ontology-driven data management.