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As AI goes mainstream a lot of us in Tech are wondering what to get into next. The mantra for now is, If you can't beat it, join it. A new role 'Forward Deployed Engineers' pioneered by Palantir, has been in huge demand and is likely to last several years as enterprises embark on their AI transformation journeys. This posting if for upcoming anticipated opportunities with top-tier frontier AI and enterprise clients. Join a growing capacity to deploy real-world AI solutions by integrating data, AI models, and intelligent workflows into customer environments. Work alongside major AI providers and enterprise software partners in Hybrid or Onsite settings across the US, UK, Canada, Australia, Ireland, and India.
You’ll help customers achieve business outcomes, validate AI outputs, and provide vital product feedback to creators and researchers while ensuring security and compliance throughout deployments.
If you have hands-on experience with AI models (LLMs), data pipelines, API integrations, and cloud infrastructure, apply now to be considered when these positions open.
Note: The compensation is an estimate based on level of experience, skills, location and other factors. |
| Typical Qualifications or Skills |
- Bachelor's degree or equivalent
- Strong software engineering background (Python, Java/Scala, Typescript/Javascript, Golang, C++, SQL)
- Experience with AI models (LLMs) and retrieval augmented generation (RAG)
- Data pipelines and ETL
- API integration with enterprise systems (CRM/ERP/Procurement/HRMS/EHR/Supplychain)
- Kubernetes and cloud infrastructure (AWS, Azure, GCP)
- LangChain, LlamaIndex, Haystack, CrewAI, Flowise n8n or similar frameworks
- Vector databases (Pinecone, Weaviate, FAISS, Milvus, Google Vertex)
- Security, compliance, tenant isolation
- Prompt engineering and iterative tuning
- Red-teaming and bias/anomaly detection
- UAT and client-side output validation
- Strong communication and client-facing skills
- DevOps and CI/CD
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| Typical Responsibilities |
- System Integration & Setup: Write custom scripts, establish data pipelines, connect AI APIs to enterprise systems
- Workflow Automation: Configure/build AI agents and automated workflows for client operations
- RAG & Infrastructure: Build data retrieval pipelines, configure vector databases, deploy Kubernetes, setup AWS/Azure/GCP infrastructure
- Security & Compliance: Ensure deployments meet customer IT & Infosec/privacy guidelines
- Tenant isolation protocols: Establish policies on multi-tenant environments to ensure data isolation.
- Product Feedback: Relay real-world user and system issues to core product/research teams
- Red-Teaming: Prompt AI models to uncover hallucinations and constraint violations
- Workflow Scoping: Assess client systems and implement a process define the boundaries, limitations, and operational rules for AI agents
- Safety Guardrails: Design policies for AI systems to operate safely and legally. Prevent AI from hallucinating, leaking proprietary data, violating compliance laws, or taking unauthorized actions
- Building evaluation criteria and scripts: Create evaluation frameworks to ensure AI model accuracy, safety, and business alignment
- UAT: Work with clients to validate output against desired results, triage issues and recommend solutions or alternatives
- Iterative Tuning: Always be tuning. Refine prompts and everything else until production-ready
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Educational Qualifications
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Typical Certifications
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| Bachelor's Degree |
- Cloud certifications (AWS, Azure, GCP) preferred
- Security/compliance certifications a plus
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Relevant Enterprise Applications
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Relevant Enterprise System Platforms
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| CRM, CPQ, ERP, CLM, HRMS, Procurement, Supplychain, EHR |
Salesforce, Stripe, Circle, Adobe, SAP, Oracle, Workday, ServiceNow, Coupa, Adobe, Stripe, data pipelines, data lakes, MDM, BI/analytics tools |
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Relevant Cloud Infrastructure Platforms
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Relevant AI Model Providers
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| AWS, MS Azure, Google Cloud Platform (GCP) |
OpenAI, Anthropic, Gemini, Cohere, Copilot, Palantir (Gotham, Foundry, AIP) |
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