GenAI Solutions Architect: LLMs, RAG & MLOps

Sia Partners; Charlotte (NC); Hybrid; USD 81,000 - 102,000; Full time

Benefits offered by this job

Healthcare coverage with multiple plan

401(k) matching

Paid time off

Parental leave

Gym reimbursement

Job summary

Sia Partners is seeking an experienced Generative AI Specialist in the United States to design, implement, and scale GenAI/LLM solutions across diverse industries. You will bridge technical teams to deliver business-centric AI value, guiding clients on RAG, agents, and fine-tuning for cost-effective impact.

Responsibilities include full AI workflow orchestration, benchmarking, prototyping, and ensuring performance, security, and scalability while tackling infrastructure challenges.

Qualifications

• Master's degree or Engineering degree in Computer Science, Engineering, Data Science, or a related quantitative field.
• 1-3+ years of hands-on experience in machine learning, software engineering, or data science, with demonstrated experience on complex AI projects specifically involving LLMs and Generative AI.
• Strong programming skills, particularly in Python.
• Proven experience in NLP/NLU, vector embeddings, and semantic search.
• Hands-on experience with fine-tuning LLMs.
• Mastery of advanced prompting techniques (Chain/Tree/Graph of Thought, ReAct, etc.).
• Knowledge of both proprietary and open-source model ecosystems (OpenAI, Anthropic, Mistral AI, Hugging Face, models hosted on AWS/Azure/GCP, etc.).
• Experience with Cloud platforms (AWS, Azure, or GCP) and their associated MLOps/AI services.
• Familiarity with MLOps principles, CI/CD tools, Docker, and Git.
• Excellent communication skills (written and verbal), ability to explain complex technical concepts simply.

Responsibilities

• LLM/GenAI System Development: Design, build, train, fine-tune, and deploy sophisticated AI models leveraging LLMs (e.g., GPT-x, Claude, Gemini, Llama, Mistral) and other generative techniques.
• Assist in Solution Architecture: Support the GenAI Solution Architect in designing robust, scalable, and secure applications.
• Application Development: Develop applications powered by GenAI models (both self-managed and API-accessible) that meet business needs and comply with applicable regulations (GDPR, EU AI Act, model licenses, etc.).
• Advanced Prompt Engineering: Design and optimize effective prompts (e.g., few-shot, Chain/Tree/Graph of Thought, ReAct, Self-reflection, guardrails), balancing simplicity and complexity to enhance analytical capabilities, refine outputs, improve user experience, and control interactions.
• RAG Implementation: Design and implement Retrieval-Augmented Generation (RAG) architectures to improve accuracy and relevance by retrieving information from pre-determined knowledge sources, providing traceability (source attribution).
• Model Selection & Fine-Tuning: Select and fine-tune appropriate models (including multimodal - VLM, SLM - Visual Language Models, Small Language Models) to create higher-quality content (text, image, audio, code, etc.) and maximize business value creation opportunities.
• Integration & Deployment (MLOps): Implement MLOps best practices for the GenAI lifecycle, including automated pipelines (CI/CD), versioning, monitoring, and maintenance in production environments (Cloud platforms like AWS, Azure, GCP). Ensure seamless integration into existing systems and with external tools/APIs, potentially utilizing standardized protocols (MCP).
• Evaluation & Responsible AI: Develop and execute rigorous evaluation frameworks to measure model performance, reliability, fairness, and safety. Ensure adherence to Responsible AI principles and help teams and clients navigate end-to-end security and compliance processes.
• Research & Innovation: Stay abreast of the latest advancements in GenAI techniques, technologies, and frameworks. Experiment with new approaches and contribute to internal knowledge sharing.
• Collaboration: Work effectively within cross-functional teams, communicating complex technical concepts clearly to diverse stakeholders (both technical and non-technical).
• Documentation: Document processes, methodologies, and best practices for knowledge sharing and future reference.
• Use Case Differentiation: Distinguish between use cases suited for Generative AI versus traditional NLP applications (e.g., NER, sentiment analysis).

Skills

Python

GenAI

LangChain

LlamaIndex

NLP/NLU

Fine-tuning LLMs

MLOps

AWS

Azure

GCP

CI/CD

Docker

Git

Education

Master's degree or Engineering degree in Computer Science / Engineering / Data Science or related field

Tools

LangChain

LlamaIndex

PyTorch

TensorFlow

Job description

Sia Partners is seeking an experienced Generative AI Specialist in the United States to design, implement, and scale GenAI/LLM solutions across diverse industries. You will bridge technical teams to deliver business-centric AI value, guiding clients on RAG, agents, and fine-tuning for cost-effective impact.

Responsibilities include full AI workflow orchestration, benchmarking, prototyping, and ensuring performance, security, and scalability while tackling infrastructure challenges.