Senior/Lead Forward Deployed AI Engineer-Anthropic-US West

highmetric; United States; Remote; USD 150,000 - 210,000; Full time

Job summary

Highmetric is seeking a Senior Forward Deployed AI Engineer to design, build, and operationalize generative AI workflow solutions directly inside enterprise environments. The role blends full‑stack development and AI delivery, translating business problems into production‑grade AI systems.

Travel approximately 70% to client sites, with remote work possibility. You will deploy AI agents, craft prompts, integrate with enterprise platforms, and ensure secure, auditable deployments.

Qualifications

• 8+ years in software engineering or related delivery roles.
• Hands-on in full-stack development, APIs, microservices, or cloud-native apps.
• Experience with AI/LLM-powered apps, RAG systems, or agentic workflows in production.

Responsibilities

• Deploy, configure, and operationalize agentic AI workflows and automations in customer environments.
• Translate business requirements into technical architectures and production plans.
• Build enterprise AI applications using LLM APIs, prompt/context engineering, RAG, tools, and human-in-the-loop patterns.
• Develop prototypes, demos, and PoCs to validate AI-driven workflows and iterate on feedback.
• Communicate AI capabilities, tradeoffs, and limitations to technical and business stakeholders.
• Contribute reusable components, prompt assets, accelerators, and feedback to internal AI platforms.

Skills

Full-stack dev

LLM Apps

Python

JavaScript

AWS

Azure

GCP

RAG

Secure deployment

APIs

Tools

LangChain

Docker

CI/CD

Git

LlamaIndex

Semantic Kernel

Job description

Role overview

A senior Forward Deployed AI Engineer is needed to design, build, and operationalize generative AI workflow solutions directly inside enterprise customer environments. The role sits at the intersection of full-stack engineering, LLM implementation, enterprise integration, and customer-facing delivery, translating real business problems into secure, reliable, production-grade AI systems. The position is remote with approximately 70% travel to client sites.

Responsibilities

• Deploy, configure, and operationalize agentic AI workflows, AI assistants, and automations inside customer enterprise platforms and surrounding technology ecosystems.
• Translate business requirements, operational processes, and desired outcomes into technical architectures, implementation plans, and production-ready AI solutions.
• Build enterprise AI applications using leading large language model APIs, applying prompt and context engineering, retrieval-augmented generation, tool use, structured outputs, multi-step orchestration, and human-in-the-loop review patterns.
• Develop prototypes, demos, and proofs of concept that validate AI-driven workflows, then iterate based on feedback, performance, and operational signals.
• Communicate AI capabilities, limitations, and tradeoffs to both technical teams and business stakeholders during discovery, workshops, pilots, and production rollouts.
• Contribute reusable components, prompt assets, accelerators, and customer-driven feedback that improve internal AI platforms and shared delivery patterns.

Requirements

• 8+ years of experience in software engineering, systems integration, enterprise platforms, workflow automation, or related technical delivery roles.
• Strong hands‑on foundation in full‑stack development, scripting, APIs, microservices, enterprise integrations, or cloud-native applications.
• Experience building or supporting AI or LLM‑powered applications, RAG systems, conversational experiences, or agentic workflows in production environments.
• Proficiency in JavaScript or TypeScript, Python, or comparable programming languages.
• Hands‑on experience with at least one major cloud platform such as AWS, Microsoft Azure, or Google Cloud.
• Working knowledge of responsible AI concepts, including hallucination mitigation, sensitive‑data handling, identity controls, human oversight, and secure deployment.

Nice to have

• Familiarity with major enterprise service management platforms and their data models, including CMDB, ITSM, CSM, HRSD, knowledge management, and workflow integrations.
• Experience with vector databases, embeddings, document ingestion, chunking, retrieval strategies, and knowledge‑grounding patterns.
• Exposure to LLM orchestration frameworks such as LangChain, LangGraph, LlamaIndex, or Semantic Kernel.
• Comfort with AI observability, tracing, evaluation frameworks, prompt and version management, and cost optimization.
• Familiarity with Docker, CI/CD, SQL, Git, infrastructure‑as‑code, and secure cloud deployment practices.

Benefits and work setup

• Remote role with approximately 70% travel to customer sites.

Inclusive, equal‑opportunity workplace with accommodations available for candidates with disabilities.