Sr. Generative AI Engineer

Senior Gen AI Engineer Harnham, a leading recruitment specialist in Data and AI, is partnering with a Databricks consulting firm that delivers enterprise-grade GenAI and LLM solutions for end clients. They are seeking a Senior Gen AI Engineer with at least five years of Databricks experience and the ability to communicate confidently with both technical and non-technical stakeholders. The ideal candidate does not need to come from a specific industry, but must have hands-on production experience with GenAI applications, including RAG systems, LLM development, or agentic frameworks. This role can be performed remotely or in a hybrid capacity from Dallas, Texas (2-3 days onsite). It is a 12-month contract with strong potential for extension, offering $85-$125 per hour for 40 hours per week. W2 employees are eligible for health, dental, vision, and 401(k) benefits. As a Senior Gen AI Engineer, you will drive end-to-end delivery of GenAI projects within the Databricks ecosystem, working closely with both Databricks teams and end clients. Responsibilities include scoping, building, and deploying GenAI solutions; developing RAG and LLM-based applications that leverage enterprise data; integrating vector databases and agentic frameworks such as LangChain; and optimizing LLM workflows for production. You will help clients productionize GenAI systems using best practices in MLOps, CI/CD, and data pipeline automation, while collaborating with broader data teams on architecture, tooling, and governance. This role also includes providing mentorship and helping clients adopt Databricks-native GenAI capabilities effectively. Qualified candidates will have 5+ years of experience in AI/ML engineering or data systems, including at least 1-2 years of hands-on GenAI production work. Strong Databricks proficiency is essential, including Spark, MLflow, and Unity Catalog. Candidates should also be skilled in Python, LangChain, OpenAI APIs, Hugging Face, and vector databases such as FAISS, Pinecone, Weaviate, or Chroma. A solid understanding of cloud platforms (AWS, Azure, or GCP) and DevOps tooling is required, along with excellent communication skills for client-facing delivery. Preferred certifications include Databricks ML Engineer, Databricks GenAI Engineer, or Databricks Data Engineer. This opportunity is ideal for someone who has successfully designed, built, and deployed generative AI solutions and wants to apply that expertise in a hands-on consulting environment. Desired Skills and Experience Databricks, RAG, LLMs, MLflow, Python