Forward Deployed AI Engineer/Anthropic – Data Intelligence-US East

Vibehackers; Northern (KY); Hybrid; USD 120,000 - 180,000; Full time

Job summary

Anthropic is seeking a Forward Deployed AI Engineer - Data Intelligence to design, build and deploy enterprise AI solutions that connect Claude and other LLMs to ServiceNow and enterprise data. This client-facing role blends AI engineering, data engineering, enterprise integration, and consulting to deliver production-ready, governed retrieval-augmented and agentic AI systems.

Location: Hybrid/Remote (flexible). Travel: up to 25–50% depending on client and business needs.

Qualifications

• 3+ years relevant engineering experience (software, AI, data, analytics, cloud, or systems integration).
• Hands-on experience building applications, data pipelines, integrations, APIs, automations, or cloud services.
• Experience with structured and unstructured data, relational databases, document repositories, APIs, and cloud storage.
• Experience with SQL, data transformation, data modeling, ETL/ELT, and data-integration concepts.
• Exposure to generative AI, LLMs, RAG, embeddings, vector search, semantic search, prompt engineering, AI agents, or LLM APIs.
• Experience building API-driven integrations using REST, JSON, OAuth, service accounts, and authentication/authorization patterns.
• Familiarity with cloud platforms (AWS, Azure, GCP).
• Understanding of software development best practices: Git, code review, testing, debugging, documentation, and agile delivery.
• Strong problem-solving and communication skills; ability to work directly with clients in consulting/professional-services engagements.

Responsibilities

• Partner with client business, data, technology, security, and ServiceNow stakeholders to identify high-value AI and Data Intelligence use cases.
• Translate requirements into technical designs, prototypes, production implementations, and iterative delivery plans.
• Build AI-enabled applications and workflows for knowledge discovery, employee assistance, service operations, document intelligence, and workflow automation.
• Design and implement data pipelines for ingestion, transformation, enrichment, indexing, and retrieval of structured and unstructured data.
• Implement RAG solutions, semantic search, embeddings, document processing, indexing, and vector storage.
• Develop prompt and context-engineering approaches, structured outputs, tool use/function calling, and agentic workflows with human-in-the-loop controls.
• Integrate AI capabilities with ServiceNow APIs, workflows, data, and user experiences.
• Implement evaluation, observability, logging, monitoring, and feedback loops across pipelines, retrieval systems, model calls, and agent workflows.
• Apply responsible AI, security, privacy, and governance controls across design, development, testing, and deployment.
• Contribute reusable components, accelerators, playbooks, and practice-level improvements for Data Intelligence delivery.

Skills

Data Engineering

AI/ML Engineering

System Integration

API Development

Cloud Engineering

RAG

Semantic Search

Vector Search

Observability

Security Governance

LLMOps

DataOps

Consulting

Problem Solving

Communication

Agile Delivery

Testing & QA

Tools

Claude

Anthropic API

ServiceNow

REST API

JSON

OAuth

Cloud Platforms

Git

Job description

Forward Deployed AI Engineer/Anthropic - Data Intelligence-US East

Directly uses Claude/Anthropic and RAG workflows; building LLM apps, connectors, and agentic AI - practical AI dev work with rapid prototyping and production focus.

About the Role

Forward Deployed AI Engineer focused on Data Intelligence, designing, building, and deploying enterprise AI solutions that connect Claude and other LLMs to ServiceNow and enterprise data. The role combines AI engineering, data engineering, enterprise integration, and client-facing consulting to deliver production-ready, governed retrieval-augmented and agentic AI systems.

Job Description

Role

Forward Deployed AI Engineer - Data Intelligence responsible for designing, building, testing, and deploying enterprise AI solutions grounded in governed, high-quality enterprise data. This client-facing role blends AI engineering, data engineering, enterprise integration, and consulting to connect Claude and other LLM technologies with ServiceNow, knowledge sources, structured data, and business workflows.

Location & Travel

Location: [Location / Hybrid / Remote] (flexible/unspecified). Travel: up to 25-50% depending on client and business needs.

Key Responsibilities

• Partner with client business, data, technology, security, and ServiceNow stakeholders to identify high-value AI and Data Intelligence use cases.
• Translate requirements into technical designs, prototypes, production implementations, and iterative delivery plans.
• Build AI-enabled applications and workflows for knowledge discovery, employee assistance, service operations, document intelligence, and workflow automation.
• Design and implement data pipelines for ingestion, transformation, enrichment, indexing, and retrieval of structured and unstructured data.
• Implement RAG solutions, semantic search, embeddings, document processing (parsing, chunking, metadata enrichment), indexing, and vector storage.
• Develop prompt and context-engineering approaches, structured outputs, tool use/function calling, and agentic workflows with human-in-the-loop controls.
• Integrate AI capabilities with ServiceNow APIs, workflows, data, and user experiences.
• Implement evaluation, observability, logging, monitoring, and feedback loops across pipelines, retrieval systems, model calls, and agent workflows.
• Apply responsible AI, security, privacy, and governance controls across design, development, testing, and deployment.
• Contribute reusable components, accelerators, playbooks, and practice-level improvements for Data Intelligence delivery.

Requirements

• 3+ years relevant engineering experience (software, AI, data, analytics, cloud, or systems integration).
• Hands-on experience building applications, data pipelines, integrations, APIs, automations, or cloud services.
• Experience with structured and unstructured data, relational databases, document repositories, APIs, and cloud storage.
• Experience with SQL, data transformation, data modeling, ETL/ELT, and data-integration concepts.
• Exposure to generative AI, LLMs, RAG, embeddings, vector search, semantic search, prompt engineering, AI agents, or LLM APIs.
• Experience building API-driven integrations using REST, JSON, OAuth, service accounts, and authentication/authorization patterns.
• Familiarity with cloud platforms (AWS, Azure, GCP).
• Understanding of software development best practices: Git, code review, testing, debugging, documentation, and agile delivery.
• Strong problem-solving and communication skills; ability to work directly with clients in consulting/professional-services engagements.

Preferred Qualifications

• Experience with Claude, Anthropic API/Console/Code or Anthropic enablement resources.
• Hands-on experience designing or implementing RAG systems and using vector databases and search technologies (e.g., Pinecone, Weaviate, pgvector, OpenSearch, Elasticsearch, Azure AI Search, Vertex AI Search).
• Familiarity with LLM application frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel.
• Experience with agentic AI, function calling, workflow orchestration, and Model Context Protocol (MCP) or secure AI-to-system integrations.
• Experience with data platforms (Snowflake, Databricks, BigQuery, Redshift, PostgreSQL, MongoDB, Microsoft Fabric).
• Experience with Docker, Kubernetes, Terraform, CI/CD, data orchestration, monitoring, and observability tools.
• Experience in enterprise consulting or professional services and relevant certifications.

Success in the First 6 Months

• Build trusted client relationships and deliver one or more Data Intelligence/AI solutions from prototype to production.
• Establish or improve secure data-ingestion, retrieval, RAG, and enterprise integration capabilities.
• Improve AI reliability via data preparation, access-aware retrieval, prompt/context engineering, testing, evaluation, and observability.
• Contribute reusable code, patterns, accelerators, and delivery playbooks to the Data Intelligence practice.

Notes

• Emphasis on secure, governed, and production-ready AI solutions connecting LLMs (Claude/Anthropic and others) with enterprise data and ServiceNow.
• Role includes significant client-facing and consulting responsibilities and may require travel.

Skills

Data Engineering AI/ML Engineering System Integration API Development Cloud Engineering Prompt/Context Engineering Retrieval-Augmented Generation (RAG) Semantic Search Vector Search/Embeddings Observability & Monitoring Security & Governance LLMOps / DataOps Consulting / Client-facing Problem Solving Communication Agile Delivery Testing & QA