- Company Name
- MM Management Consultant
- Job Title
- Gen AI Solution Architect
- Job Description
-
Job title: Gen AI Solution Architect
Role Summary: Design, develop, and deploy production-grade generative AI solutions leveraging large language models (LLMs), RAG pipelines, and cloud infrastructures. Lead cross-functional teams in integrating AI services with enterprise systems via APIs and microservices, ensuring scalability, performance, and security.
Expactations: Deliver end-to-end AI architecture solutions on a contract or full‑time basis, mentor engineering teams, evaluate emerging GenAI technologies, and optimize cost‑effective cloud deployments.
Key Responsibilities:
- Architect scalable generative AI systems using LLMs, LangChain, LlamaIndex, or equivalent orchestration frameworks.
- Build, test, and deploy AI pipelines in Python, employing modern ML libraries.
- Integrate AI models with enterprise applications through RESTful APIs and microservices.
- Optimize prompts, embedding strategies, and RAG pipelines for accuracy and speed.
- Deploy and manage AI workloads on AWS, Azure, or GCP, ensuring reliability, security, and cost efficiency.
- Mentor engineering teams on best practices in AI architecture, coding standards, and deployment workflows.
- Assess new GenAI tools, frameworks, and model releases, recommending adoption strategies aligned with business goals.
Required Skills:
- 12+ years of professional experience in AI/ML roles.
- Deep expertise in generative AI and LLMs (OpenAI, Anthropic, Llama, Mistral).
- Proficient in Python and experienced with ML frameworks (PyTorch, TensorFlow, Hugging Face).
- Hands‑on experience with RAG architectures and vector databases (Pinecone, Weaviate, FAISS, Chroma).
- Strong prompt engineering and model evaluation capabilities.
- Proven ability to design and implement cloud‑based AI solutions on AWS, Azure, or GCP.
- Understanding of data engineering, ML pipelines, and scalable system architecture.
Required Education & Certifications:
- Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field.
- Relevant certifications such as AWS Certified Solutions Architect, Azure AI Engineer Associate, or equivalent credentials in cloud AI services.