Senior Generative AI Engineer

Harnham • Contract • Remote (Dallas, Texas, United States) • $85 - $125 / hour • 22h ago

Harnham, the leading recruitment specialist in Data and AI is currently partnering with a Databricks consulting partner delivering enterprise-grade GenAI and LLM solutions for end clients.

They are in need of a Sr Gen AI Engineer who has at least 5 years of experience with Databricks and who is comfortable communicating with both technical and non-technical stakeholders.

The ideal hire does not necessarily need to come form a specific company or industry, however, *hands-on GenAI production experience (RAG, LLMs, or agentic frameworks)* is a MUST.

Role - Sr. Gen AI Engineer
Location - Remote - OR - Hybrid (2-3 days on-site) in Dallas, Texas
Pay - $85-$125 per hour
Length: Extendable, 12 months initial contract
Utilization: 40 hr/week
Benefits: W2 employees are eligible to health, dental, vision, 401k benefits.

As a Sr Gen AI engineer, you will be a key player in driving project completion and working extensively with both Databricks and the end-client on your projects.

Key Responsibilities:

Deliver end-to-end GenAI projects on the Databricks platform, from scoping through build and deployment.
Develop RAG (Retrieval-Augmented Generation) and LLM-based applications that utilize enterprise data and knowledge repositories.
Implement vector database solutions, integrate LangChain / agentic frameworks, and optimize LLM workflows.
Support clients in productionizing GenAI systems with best practices for MLOps, CI/CD, and data pipeline automation.
Collaborate with data teams to design scalable architectures and advise on tooling, deployment, and governance.
Provide mentorship to broader ML teams and help clients adopt Databricks-native GenAI solutions effectively.

Requirements:

5+ years of overall experience in AI/ML engineering or data systems.
1-2 years of proven, hands-on GenAI production experience (RAG, LLMs, or agentic frameworks).
Strong Databricks expertise - all delivery occurs within the Databricks ecosystem (Spark, MLflow, Unity Catalog, etc.).
Proficiency in Python, LangChain, OpenAI API, Hugging Face, and vector DBs such as FAISS, Pinecone, Weaviate, or Chroma.
Strong grasp of cloud deployment (AWS, Azure, GCP) and DevOps pipelines (Git, Azure Pipelines, CI/CD).
Excellent communication skills for client-facing consulting and delivery engagements.
Preferred certifications: Databricks Associate/Professional ML Engineer, Databricks GenAI Engineer, or Databricks Data Engineer.

This is an excellent opportunity for someone who has designed, developed, and deployed generative AI solutions and wants to leverage that expertise as a hands-on consultant.

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