What are the responsibilities and job description for the Generative AI Engineer position at Crossing Hurdles?
Crossing Hurdles is a global recruitment firm that partners with US-based companies to help them hire high-quality talent across technology and business functions. We work closely with fast-growing teams to identify professionals who can deliver impact in complex, high-ownership roles.
Location: On-site, Richardson, TX
Employment Type: Full-Time
Seniority: Mid-Senior to Senior
Experience: 8 years overall (2–3 years in GenAI/AI systems)
About the Role
As a Generative AI Engineer, you will be a core member of a high-impact engineering pod, responsible for building and integrating agentic AI systems powered by advanced LLM and Generative AI technologies. You will collaborate closely with Tech Leads and Full Stack Engineers to convert AI capabilities into production-ready, enterprise-grade solutions.
What You’ll Be Working On
- Designing, developing, and deploying agentic AI systems using modern LLM frameworks
- Integrating Generative AI models into full-stack applications and internal workflows
- Collaborating on prompt engineering, model fine-tuning, and evaluation
- Building reusable components for multi-agent orchestration and task automation
- Optimizing AI inference pipelines for scalability, latency, and cost efficiency
- Participating in architectural discussions and contributing to the technical roadmap
Must-Have Experience
- 8 years of software engineering experience
- 2–3 years of hands-on experience with AI/ML or Generative AI systems in production
- Strong experience using Python for AI/ML integration
- Hands-on with LangChain and LlamaIndex
- Experience with agentic frameworks such as LangGraph or Google ADK
- Understanding of Git, CI/CD, DevOps, and production-grade AI deployment
- Familiarity with Google Cloud Platform (Vertex AI, Cloud Run, GKE)
Nice to Have
- Experience with embeddings, vector databases, and AI APIs
- Fine-tuning open-source LLMs (LLaMA, Mistral) or working with OpenAI APIs
- Exposure to multimodal AI systems (text, image, voice)
- Familiarity with low-code/no-code workflow tools
Why This Role
- Work on real-world, production AI systems
- High ownership and hands-on technical impact
- Opportunity to build and scale enterprise-grade GenAI solutions
- Collaborate with senior engineers on complex AI problems