Explicitly requires Vibe coding skills and uses AI code-generation to build rapid PoCs/MVPs with LLM pipelines.
About the Role
Technical AI Solution Engineer to design, architect, and implement AI and Generative AI solutions, rapidly build PoCs/MVPs, and lead solutions from ideation to production. Requires hands-on work with LLMs, Vibe coding, embeddings, retrieval, agents, and cloud integrations. Part-time contract (3–6 months) based in Plano, TX with the option to convert to full-time.
Job Description
Role
A Technical AI Solution Engineer responsible for designing, architecting, developing, and delivering AI and Generative AI solutions across customer needs. The role focuses on translating business challenges into scalable AI-driven solutions, rapidly building PoCs/MVPs, and leading the full solution lifecycle from ideation to production. This is a part-time contract role (3–6 months) based in Plano, TX with an option to convert to full-time.
Key Responsibilities
- Lead end-to-end design of AI and Generative AI solutions, including system architecture, data flows, model selection, and integration patterns.
- Partner with customers, product managers, and business teams to identify high-impact AI-driven use cases and recommend solution approaches.
- Evaluate AI technologies, frameworks, and vendors.
- Build proofs of concept (PoC), MVPs, and production-grade features using Vibe coding, LLMs, embeddings, retrieval, agents, and advanced AI pipelines.
- Implement AI workflows such as MCP, RAG, finetuning, prompt engineering, and agentic orchestration; perform model optimization.
- Develop integrations with enterprise systems, APIs, data platforms, and cloud environments (AWS/Azure/GCP).
- Serve as a subject-matter expert and advisor on modern AI, GenAI, and LLM-based architectures; conduct demos, workshops, and knowledge-sharing sessions.
Requirements
- Strong hands-on experience with LLMs and GAI frameworks (OpenAI, Azure OpenAI, Anthropic, Meta Llama).
- Experience building AI pipelines using MCP/RAG architectures, agent/multi-agent orchestration, prompt engineering and evaluation, and finetuning or parameter-efficient training (LoRA, adapters).
- Proficiency in Vibe coding and AI code-generation tools.
- Proficiency in Python and/or Node.js; familiarity with LangChain, Semantic Kernel, and LlamaIndex.
- Experience with ML frameworks (PyTorch; TensorFlow optional).
- Experience with vector databases and retrieval tooling such as Pinecone, Weaviate, Chroma, and Redis Vector; experience with embeddings.
- Knowledge of cloud AI services (Azure, AWS, Google Cloud Platform) and strong understanding of API architectures, microservices, DevOps, CI/CD, and containerization.
- Background: 5–10+ years in software or solution engineering and 2–3+ years specifically in AI/ML or GenAI implementation. Bachelor’s or Master’s in Computer Science, Engineering, AI/ML, or related field.
Preferred Qualifications
- Experience with telco and media or large enterprise environments.
- Knowledge of data engineering, ETL pipelines, feature stores, MLOps/LLMOps methodologies and tools.
- Exposure to vector search optimization, knowledge graphs, or reinforcement learning.
- Familiarity with responsible AI, security, governance, and compliance frameworks.
Logistics
- Location: Plano, TX
- Role type: Part-time with option to convert to full-time
- Duration: 3–6 months
- Contact: hirings@openkyber.com