Forward Deployed Engineer IV

Jobtailor

San Antonio (TX)

On-site

USD 140,000 - 190,000

Full time

14 days+

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Benefits offered by this job

Job summary

Jobtailor is seeking an experienced Enterprise AI Engineer to diagnose business challenges, map data landscapes, and co-design AI solutions on-site in a client-facing capacity. You will lead end-to-end solution design for agentic AI workflows, RAG pipelines, and knowledge graphs, delivering rapid POCs that prove business value within days to weeks.

You will own the full project lifecycle from scoping to deployment, architect production-grade AI apps on Foundry or private cloud platforms, and

Qualifications

Degree in CS/Engineering or related technical field required.
Palantir Certification is mandatory.
6+ years in software/data/AI delivery with customer-facing experience.
Proven production deployment of AI/ML at enterprise scale.
Strong full-stack proficiency and data/integration experience.

Responsibilities

Diagnose business challenges, map data landscapes, and co-design AI solutions on-site.
Lead end-to-end design and delivery of AI workflows, RAG pipelines, and knowledge graphs.
Drive rapid prototyping and POCs showing tangible value within days to weeks.
Own the full project lifecycle: scoping, architecture, build, deployment, and optimization.
Architect Enterprise AI apps on Foundry or private clouds, integrating ERP/CRM systems.

Skills

Palantir Certification

Full-Stack Proficiency

DevOps Skills

LLMs & RAG Architectures

Domain Expertise

Prompt Engineering

Model Fine-Tuning

Knowledge Graphs

Agent Orchestration

Education

Bachelor’s degree in CS/Engineering

Tools

Palantir Foundry

GPU Infrastructure

Private Cloud Platforms

Vector Databases

Streaming Architectures

Job description

Diagnose critical business challenges, map data landscapes, and co-design AI solutions on-site
Lead end-to-end solution design and delivery of agentic AI workflows, RAG pipelines, knowledge graphs, and real-time decision-making applications
Drive rapid prototyping and POCs that demonstrate tangible business value within days to weeks
Serve as the primary technical owner across the full project lifecycle: scoping, architecture, build, deployment, and post-launch optimization
Architect production-grade Enterprise AI applications on Partner Foundry Solutions or Rackspace Private Cloud and GPU infrastructure, integrating with enterprise systems (ERP, CRM, data warehouses, data lakes)
Build scalable data pipelines across structured and unstructured data using ETL/ELT, vector databases (Pinecone, Weaviate, AstraDB), and knowledge base frameworks
Develop and fine-tune LLM/SLM solutions; implement RAG architectures (LlamaIndex, Haystack) and orchestrate multi-agent workflows (LangChain, LangGraph, CrewAI)
Ship with full-stack and DevOps depth: Python, Node.js/Go, React/Vue, Docker, Kubernetes, CI/CD, and GPU cluster management
Champion observability, monitoring, and telemetry to ensure trustworthy, auditable, and versioned AI agents in production
Identify expansion opportunities by working with sales and customer success to uncover high-value use cases across new business domains
Feed structured field insights back to Platform Engineering and Product on feature gaps, emerging needs, and usability improvements
Build reusable IP through reference architectures, accelerators, frameworks, and technical best practices that scale future engagements
Mentor engineers and customer teams, driving knowledge transfer and building internal AI competencies.

Requirements

Bachelor’s degree in computer science, engineering, or related technical discipline required
Must be Palantir certified
6 + years in software engineering, data engineering, or AI/ML delivery; at least 4+ years in customer-facing or field roles
Proven track record in building and deploying AI/ML applications in production at enterprise scale
Deep full-stack proficiency: Python (required), Node.js/Go, React/Vue, SQL/NoSQL databases
Hands-on with LLMs, prompt engineering, vector databases, data pipelines, application dashboards, RAG pipelines, and agent orchestration frameworks
Strong DevOps skills: Docker, Kubernetes, CI/CD, GPU infrastructure, cloud-native deployment patterns
Experience integrating across heterogeneous enterprise systems - ERP, data warehouses, data lakes, streaming architectures
Ability to translate ambiguous customer needs into actionable engineering plans under tight timelines
Excellent communication skills
Experience with Palantir Foundry, AIP, ontology modeling, Uniphore BAIC, or similar Enterprise AI development platforms
Knowledge of SLM fine-tuning, model distillation, RLHF, and AI evaluation frameworks
Experience building agentic AI solutions: multi-agent systems, tool use, and autonomous workflow orchestration
Familiarity with GPU infrastructure (NVIDIA H100/B200, InfiniBand) and private cloud platforms (OpenStack, VMware)
Prior experience in technology consulting, AI startups, or Forward Deployed / Solutions Engineering roles
Domain expertise in financial services, healthcare, supply chain, defense, energy, or manufacturing
Experience with knowledge graphs, semantic modeling, and ontology-driven data management.

Core Competencies

Demonstrates expertise in architecting and deploying Enterprise AI applications, with a strong focus on full-stack development, data engineering, and AI/ML solutions. Proven ability to lead technical projects, mentor teams, and translate customer needs into actionable engineering plans.

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