What are the responsibilities and job description for the AI Engineer position at Elios?
AI Engineer — GenAI / Agentic Systems (Contract)
AI Engineering | Contract | Dallas, TX | Onsite 5 days/week
About the Role
We are partnering with a global consulting firm to bring on an AI Engineer focused on GenAI and agentic systems. You will build LLM-powered applications and autonomous AI agents that integrate with enterprise data and actually make it to production. The team is hands-on, modern, and operating at the front edge of GraphRAG, agent frameworks, and LLMOps.
This is a builder seat. You will design systems, write the code, ship to AWS/Azure/GCP, evaluate models with real frameworks, and help shape the architecture along the way. The right person here has shipped LLM systems in production and knows the difference between a demo and something that holds up under load.
What You Will Own
- Build GenAI applications leveraging foundation models and advanced architectures such as GraphRAG.
- Develop autonomous AI agents using modern agentic frameworks.
- Design and deploy RAG and GenAI services using Python (FastAPI), Docker, and cloud platforms (AWS, Azure, or GCP).
- Build scalable REST APIs that power LLM-driven applications integrated with enterprise data sources.
- Implement LLM evaluation frameworks using tools such as Ragas, LangSmith, or custom benchmarks to measure answer relevance, groundedness, and hallucination rates.
- Apply LLMOps/MLOps practices, including CI/CD pipelines, prompt/version management, automated testing, and monitoring of latency, cost, and response quality.
- Develop systems leveraging embeddings at scale, knowledge graphs, and ontology extraction.
- Collaborate across engineering teams, mentor developers, and help drive innovation in GraphRAG and agentic AI architectures.
What You Bring
Must-Haves
- 5 years of AI/ML-focused software engineering experience.
- Production experience building LLM-based or agentic AI systems.
- Strong expertise in Python and modern AI frameworks.
- Experience with embeddings, knowledge graphs, ontology extraction, and advanced RAG/GraphRAG implementations.
- Full-stack development and deployment experience (Python back end with a modern front end).
- Experience deploying AI workloads to AWS, Azure, or GCP.
- Familiarity with LLMOps/MLOps tooling and model evaluation frameworks.
- Strong problem-solving, communication, and collaboration skills.
Education
- Degree in Computer Science, AI/ML, or a related field.
About the Firm
Our partner is a global consulting firm that builds technology and data platforms for the world's largest financial services and enterprise clients. The AI work here is real, in production, and reaches end users.
Why This Role
- Hands-on GenAI and agentic systems work, not slideware.
- Real ownership across the AI engineering lifecycle, from architecture to evaluation to deployment.
- A team building at the front edge of GraphRAG and agent frameworks.
- Onsite collaboration in Dallas with a sharp engineering bench.
- Contract engagement with a modern stack and meaningful enterprise impact.