AI Engineer - EAI

Title: AI Engineer - EAI Location: Plano TX Duration: 1 year Contract Position Summary: We are seeking a highly motivated and experienced AI Engineer – EAI with 5 years of experience to join our dynamic Business Support team. This position is ideal for a candidate with strong hands-on AI engineering and research experience, particularly in Generative AI, LLMs, agent frameworks, and rapid prototyping, who can translate emerging technologies into practical business solutions. The successful candidate will be responsible for researching and evaluating new AI technologies, building proof-of-concept solutions, developing and testing GenAI workflows and agentic systems, benchmarking models and frameworks, and collaborating with engineering teams to transition prototypes into scalable production-ready solutions. Requirements Essential Functions: Description / Essential Functions: • AI Research & Emerging-Tech Exploration • Continuously research advancements in AI/ML, with a strong focus on Generative AI, LLM architectures, agent frameworks, and multimodal models. • Evaluate emerging tools, frameworks, and APIs such as ChatGPT, GitHub Copilot, Lang Chain, Lang Smith, CrewAI, vector DBs, RAG frameworks, orchestration tools, and model hosting platforms. • Identify opportunities where new AI capabilities can solve business problems or streamline client’s operations. Rapid Prototyping & Hands-On Development • Build rapid, functional prototypes with a strong hands-on coding approach using Python, modern AI SDKs, and model APIs. • Develop experimental features and concepts that validate feasibility before engineering teams take them to production. • Design, test, and iterate on AI workflows, pipelines, agentic systems, and retrieval-augmented applications. Technical Experimentation & Evaluation • Conduct benchmarking, model evaluation, prompt engineering, and fine-tuning experiments to assess performance. • Compare models, frameworks, and architectures to recommend best-fit technologies for production teams. • Document findings with clarity, experiment logs, model performance summaries, reproducible code samples, and technical write-ups. Collaboration With Engineering & Stakeholders • Work hand-in-hand with engineering teams to transition prototypes into scalable production-ready systems. • Translate experimental results into actionable recommendations for architecture, infrastructure, and model deployment. • Engage with product managers, business partners, and data scientists to align prototypes with real-world needs. Thought Leadership & Knowledge Sharing • Track market activity, academic research, open-source contributions, and competitor innovation trends. • Present insights, demos, and proposals to technical leadership and stakeholders. • Foster a culture of AI innovation through workshops, documentation, and internal knowledge sharing. Minimum qualification: Required Education & Experience: Technical & Research Expertise • Bachelor’s degree (or equivalent experience) in Computer Science, AI, Data Science, or a related technical field. • 5+ years of hands-on experience in AI engineering, research engineering, ML prototyping, or similar roles. • Strong programming proficiency in Python and familiarity with major AI/ML frameworks (TensorFlow, PyTorch). • Practical experience with LLMs, prompt engineering, RAG systems, Lang Chain, Lang Smith, CrewAI, vector databases, and other modern GenAI tools. • Experience building rapid prototypes, POCs, and experimental AI applications. Applied AI & Tooling Knowledge • Deep understanding of AI ecosystems such as OpenAI, Anthropic, Hugging Face, Azure AI, AWS Bedrock, etc. • Familiarity with developer tools like GitHub Copilot, GPT-based coding assistants, and modern MLOps workflows. • Comfort exploring model internals, parameter tuning, API integrations, and evaluation frameworks. Soft Skills & Collaboration • Strong ability to translate cutting-edge research concepts into practical technical solutions. • Excellent communication and documentation skills for both technical and non-technical audiences. • Curiosity-driven mindset and commitment to daily research, experimentation, and continuous learning. • Ability to manage multiple research tracks, prototypes, and fast-moving developments. Preferred qualification: • Experience with fine-tuning, LoRA, or custo • Background in agentic AI systems, automation frameworks, and workflow orchestration. • Prior experience publishing research insights or contributing to open-source AI projects. • Certifications in advanced AI/ML topics or cloud AI platforms.