AI Engineer

Overview

AI Engineer

Location:
Plano, Texas – ONSITE
Only Local Candidates
NO Fake Resumes – ONLY Genuine Experienced Candidates Needed – No Fabricated Resumes
Only US Citizens

Requirements — 10 years of software engineering and development experience; degree in Computer Science, Artificial Intelligence, Data Analytics, or equivalent field (or comparable background); over 5 years of direct involvement in AI development, investigative roles, ML experimentation, or related positions.

Must-Have Skills

• Python
• AI/ML frameworks (Tensor Flow / PyTorch)
• LLMs & Generative AI
• Prompt Engineering
• RAG & Vector Databases
• AI Platform Experience (OpenAI, Hugging Face, Anthropic)
• Prototyping & AI Tool Development
• Lang Chain / CrewAI
• AWS Bedrock / Azure AI
• MLOps & CI/CD
• LoRA Fine-Tuning
• Agentic AI Systems
• Open-source contributions

We are looking for a driven and technically proficient AI Engineer who thrives on the latest AI innovations, quick iteration, and converting innovative concepts into practical applications that enhance AI integration throughout our client’s business processes.

This position reports to the AI Product & Research Manager and involves investigating advancements in Generative AI, creating initial prototypes, and partnering with development teams to evolve these into robust, deployable solutions.

• AI Innovation and Technology Assessment
• Stay abreast of developments in AI and Machine Learning, emphasizing Generative AI, large language model structures, agent-based systems, and multi-modal approaches.
• Assess new technologies, libraries, and interfaces including platforms like ChatGPT, Git Hub Copilot, Lang Chain, Lang Smith, CrewAI, vector stores, retrieval-augmented generation tools, workflow managers, and model deployment services
  .
• Pinpoint areas where innovative AI features can address operational challenges or improve efficiency in the client’s environment.

• Rapid Prototyping & Hands-On Development
• Construct efficient, operational prototypes with a strong hands-on coding approach in Python, utilizing contemporary AI toolkits and model APIs.
• Create trial functionalities and ideas to confirm viability prior to handover to production engineering groups.
• Develop, evaluate, and refine AI processes, data pipelines, autonomous systems, and applications enhanced by retrieval mechanisms.

• Experimentation and Evaluation
• Perform comparative testing, model assessments, prompt optimization, and adjustment trials to measure effectiveness.
• Analyze various models, tools, and designs to suggest optimal solutions for implementation teams.
• Record outcomes clearly, including experiment records, performance overviews, replicable scripts, and detailed technical write-ups.

• Teamwork with Developers and Partners
• Collaborate directly with development groups to convert prototypes into reliable, production-grade platforms.
• Convert test results into practical guidance on system design, resources, and deployment strategies.
• Interact with product leads, business collaborators, and analytics experts to ensure prototypes meet practical requirements.

• Innovation Advocacy and Information Dissemination
• Monitor industry trends, scholarly publications, community contributions, and competitive advancements.
• Deliver presentations, demonstrations, and suggestions to technical executives and key stakeholders.
• Promote an environment of AI advancement via training sessions, guides, and shared internal resources.

• Technical Proficiency and Investigative Skills
• Degree in Computer Science, Artificial Intelligence, Data Analytics, or equivalent field (or comparable background).
• Over 5 years of direct involvement in AI development, investigative roles, ML experimentation, or related positions.
• Advanced coding skills in Python and knowledge of primary AI/ML environments (e.g.,
  Tensor Flow, Py Torch ).
• Hands-on involvement with LLMs, prompt refinement, retrieval-augmented systems, Lang Chain, Lang Smith, CrewAI, vector databases
  , and similar contemporary Generative AI resources.
• Track record in developing rapid prototypes, proofs-of-concept, and trial AI tools.

• Practical AI and Ecosystem Familiarity
• Thorough insight into AI…