Explicitly requires vibe coding and use of AI code generation tools for rapid prototyping and PoC/MVP development.
About the Role
Lead the design, architecture, and hands-on delivery of AI and Generative AI solutions, building PoCs/MVPs and production integrations to solve customer problems. Contract role (3–6 months, hybrid in Dallas or Atlanta) requiring rapid prototyping, solution engineering, and deployment across cloud environments.
Job Description
Role
Technical AI Solution Engineer responsible for designing, architecting, developing, and delivering AI and Generative AI solutions across customer use cases. The role combines solution architecture, hands-on development of PoCs/MVPs, and end-to-end delivery from ideation to production.
Location & Duration
- Hybrid: Dallas, TX or Atlanta, GA
- Contract: 3–6 months
- Expected time commitment: approximately 3–6 hours per day
Key Responsibilities
- Lead end-to-end AI and GenAI solution architecture, including system design, data flows, model selection, and integration patterns.
- Partner with customers, product managers, and business teams to identify high-impact AI use cases and translate business needs into technical designs.
- Rapidly build proofs of concept (PoC) and MVPs using LLMs, embeddings, retrieval, agents, and advanced AI pipelines.
- Implement AI workflows such as MCP, RAG, fine-tuning (LoRA/adapters), prompt engineering, and agentic orchestration.
- Integrate solutions with enterprise systems, APIs, data platforms, and cloud environments (Azure/AWS/GCP).
- Serve as a subject-matter expert and advisor on modern AI/LLM architectures, vector databases, and agentic automation.
- Conduct demos, workshops, and knowledge-sharing sessions as needed.
Required Skills & Experience
- Strong hands-on experience with LLMs and GenAI frameworks (OpenAI, Azure OpenAI, Anthropic, Meta Llama, etc.).
- Experience implementing MCP/RAG architectures, multi-agent orchestration, prompt engineering, and fine-tuning techniques.
- Proficiency with Vibe coding and AI code generation tools.
- Proficiency in Python and/or Node.js and experience with LangChain, Semantic Kernel, or LlamaIndex.
- Familiarity with ML frameworks (PyTorch, TensorFlow optional).
- Experience with vector databases (Pinecone, Weaviate, Chroma, Redis Vector).
- Knowledge of cloud AI services (Azure, AWS, Google Cloud Platform) and experience with API architectures, microservices, DevOps, CI/CD, and containerization.
- Strong communication, documentation, and solution delivery skills; experience interacting with customers and presenting technical solutions.
Preferred Qualifications
- Experience in telco, media, or large enterprise environments.
- Background in data engineering, ETL pipelines, feature stores, MLOps/LLMOps methodologies and tools.
- Exposure to vector search optimization, knowledge graphs, reinforcement learning, and responsible AI/security/governance practices.
What We Offer
- Opportunity to build impactful AI solutions at scale and participate in next-generation AI innovation.
- Collaborative and supportive working environment.