Forward Deployed AI Engineer-Anthropic-US East

highmetric; United States; Remote; USD 180,000 - 260,000; Full time

Benefits offered by this job

Remote-first

Travel opportunities

Inclusive workplace

Job summary

highmetric is seeking a senior forward-deployed AI engineer to turn frontier LLM capabilities into production-ready enterprise workflows. You will work across full-stack engineering, enterprise integration, and applied generative AI, partnering with customer teams to deploy and scale AI-powered automations.

The role blends hands-on technical work with client-facing delivery, including roughly 25% travel to customer sites.

Qualifications

• 5-8 years of experience in software engineering, systems integration, enterprise platforms, or related technical delivery roles.
• Proficiency in JavaScript/TypeScript or Python and cloud platforms (AWS, Azure, or Google Cloud).
• Experience building or deploying LLM-powered applications, AI-enabled automations, RAG systems, or agentic workflows.
• Familiarity with prompt engineering, embeddings, vector search, tool use, structured outputs, and model evaluation.
• Understanding of responsible AI: data handling, hallucination mitigation, identity controls, secure deployment.

Responsibilities

• Deploy, configure, and operationalize agentic AI workflows and automations within customer environments.
• Translate business requirements into technical architectures, implementation plans, and production-grade solutions.
• Build retrieval-augmented generation systems grounded in enterprise data with prompts and human-in-the-loop reviews.
• Integrate reusable AI accelerators and workflow components into client environments with custom tailoring.
• Lead discovery sessions, workshops, pilots, and production rollouts, communicating capabilities and tradeoffs.
• Contribute reusable components and feedback to internal AI platforms and accelerators.

Skills

JavaScript/TypeScript

Python

AWS

Azure

Google Cloud

LLM-powered apps

Customer-facing delivery

Tools

LangChain

LangGraph

LlamaIndex

Semantic Kernel

Docker

CI/CD

Job description

Role overview

A senior forward-deployed AI engineering role focused on turning frontier large language model capabilities into production-ready enterprise workflow solutions. The position sits at the intersection of full-stack engineering, enterprise integration, and applied generative AI, partnering directly with customer teams to deploy, operationalize, and scale AI-powered automations. Expect a blend of hands-on technical implementation and client-facing delivery, with roughly 25% travel to customer sites.

Responsibilities

• Deploy, configure, and operationalize agentic AI workflows, assistants, and automations within customer enterprise service management environments and connected technology ecosystems.
• Translate business requirements and operational processes into technical architectures, implementation plans, and production-grade AI solutions.
• Build retrieval-augmented generation systems grounded in authorized enterprise data, and apply prompt and context engineering, tool use, structured outputs, and human-in-the-loop review patterns.
• Integrate reusable AI accelerators, agent packs, and workflow components into enterprise environments, tailoring them to client operating models, data sources, and security needs.
• Lead discovery sessions, technical workshops, pilots, and production rollouts, communicating capabilities, limitations, and tradeoffs to both technical and business stakeholders.
• Contribute reusable components, implementation patterns, and customer-driven feedback back into internal AI platforms and accelerators.

Requirements

• 5-8 years of experience in software engineering, systems integration, enterprise platforms, or related technical delivery roles.
• Hands-on proficiency in JavaScript/TypeScript, Python, or comparable languages, plus experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Demonstrated experience building or deploying LLM-powered applications, AI-enabled automations, RAG systems, or agentic workflows.
• Familiarity with modern LLM application concepts, including prompt engineering, embeddings, vector search, tool use, structured outputs, and model evaluation.
• Understanding of responsible AI practices, including hallucination mitigation, sensitive-data handling, identity controls, human oversight, and secure deployment.
• Customer-facing engineering, consulting, or solutions architecture experience with the ability to navigate complex stakeholder environments.

Nice to have

• Experience with enterprise service management platform development, including CMDB data models, ITSM/CSM/HRSD workflows, knowledge management, and integration patterns.
• Familiarity with orchestration frameworks such as LangChain, LangGraph, LlamaIndex, or Semantic Kernel.
• Experience with vector databases, document ingestion pipelines, AI observability tooling, and prompt/version management.
• Comfort with Docker, CI/CD, SQL, Git, and infrastructure-as-code practices.

Benefits and work setup

• Remote-first arrangement with approximately 25% travel to customer sites.
• Opportunity to shape and contribute to internal AI platforms, accelerators, and reusable assets.
• Inclusive, equal-opportunity workplace with accommodations available for candidates with disabilities.