Dew SoftwareDallas, TX or Atlanta, GA (Hybrid)
Contract – W2
AI Solution Architecture & Design
Design end-to-end AI and Generative AI solutions including architecture, data flows, model selection, and integrations.
Partner with business stakeholders, product teams, and customers to identify high-impact AI use cases.
Evaluate AI technologies, frameworks, and vendors to recommend optimal solution approaches.
Define scalable and secure enterprise AI architectures.
Hands-On Development & Implementation
Build PoCs, MVPs, and production-ready AI solutions using LLMs and advanced AI pipelines.
Implement AI workflows such as RAG, MCP, fine-tuning, prompt engineering, agentic orchestration, and model optimization.
Develop integrations with enterprise systems, APIs, data platforms, and cloud services.
Utilize modern AI coding tools and automation to accelerate development.
Technical Leadership & AI Evangelism
Act as a subject matter expert for AI/GenAI technologies and LLM-based architectures.
Stay current with emerging AI infrastructure, vector databases, and agentic frameworks.
Conduct technical demos, workshops, and knowledge-sharing sessions with clients and internal teams.
Provide architectural guidance and best practices across AI initiatives.
Required Skills & Experience
AI / GenAI Technical Skills
Strong hands-on experience with LLMs and GenAI platforms (OpenAI, Azure OpenAI, Anthropic, Meta Llama, etc.).
Experience with RAG architectures, AI agents, and multi-agent orchestration.
Prompt engineering, evaluation strategies, and model optimization techniques.
Fine-tuning or parameter-efficient training (LoRA, adapters, etc.).
Programming & Development
Strong programming skills in Python and/or
Experience with frameworks such as LangChain, Semantic Kernel, or LlamaIndex.
Familiarity with ML frameworks (PyTorch or TensorFlow – optional but preferred).
Experience with vector databases (Pinecone, Weaviate, Chroma, Redis Vector).
Cloud & Engineering Practices
AWS, Azure, or GCP.
Strong knowledge of APIs, microservices, DevOps practices, CI/CD pipelines, and containerization.
Experience integrating AI solutions into enterprise applications.
Solution Engineering & Consulting
Ability to translate business requirements into scalable AI solutions.
Strong communication, architecture documentation, and presentation skills.
Experience working directly with customers and cross-functional teams.
5–10+ years of experience in software engineering or solution engineering.
2–3+ years of hands-on AI/ML or GenAI implementation experience.
Bachelor's or Master's degree in Computer Science, Engineering, AI/ML, or a related field.
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