Generative AI Consultant

# Generative AI Consultant

## About the Role

Sia is seeking a skilled and business-focused **Generative AI Consultant** to join its AI & Data Business Unit. This role focuses on helping clients design, build, and implement Generative AI and Large Language Model solutions that create measurable business value across industries.

The Generative AI Consultant will work at the intersection of strategy, technology, data science, machine learning, platform engineering, and client delivery. This person will help clients understand what is possible with GenAI, identify practical use cases, select the right technical approach, and guide AI products from early benchmarking and prototyping through deployment, validation, and ongoing improvement.

This role is ideal for someone who can bridge business goals and technical execution. The consultant should be comfortable working with client stakeholders, data science teams, machine learning engineers, platform engineers, product teams, and leadership groups to design AI solutions that are useful, scalable, secure, and aligned with business needs.

## Key Responsibilities

* Design, build, train, fine-tune, and deploy AI models and applications using large language models and Generative AI technologies.
* Help clients identify, prioritize, and implement GenAI use cases that support business value, operational improvement, automation, decision support, customer experience, and knowledge management.
* Serve as a bridge between business stakeholders and technical teams, including Data Science, Machine Learning, Platform Engineering, Product, and IT teams.
* Guide clients on appropriate GenAI approaches, including retrieval-augmented generation, agent-based workflows, fine-tuning, prompt engineering, model orchestration, and hybrid AI architectures.
* Support AI products from discovery, benchmarking, prototyping, and proof-of-concept development through deployment, validation, and production adoption.
* Assist in designing robust AI applications that are scalable, reliable, secure, and aligned with enterprise requirements.
* Develop applications powered by GenAI models, including chat-based tools, knowledge assistants, document analysis systems, workflow automation tools, summarization systems, classification tools, and recommendation engines.
* Implement MLOps and LLMOps practices across the GenAI lifecycle, including versioning, testing, evaluation, deployment, monitoring, governance, and continuous improvement.
* Evaluate model performance, output quality, hallucination risk, retrieval quality, latency, cost, reliability, and business usefulness.
* Develop prompt strategies, structured output pipelines, model evaluation methods, and validation workflows.
* Work with embeddings, vector databases, search strategies, data pipelines, APIs, cloud services, and model-serving platforms to support GenAI solutions.
* Collaborate with client teams to define solution architecture, implementation roadmaps, technical requirements, and success metrics.
* Translate complex AI concepts into clear recommendations for business leaders and non-technical stakeholders.
* Participate in workshops, stakeholder interviews, solution design sessions, and technical working sessions.
* Document AI architecture, model choices, prompt designs, evaluation criteria, technical assumptions, risks, and implementation decisions.
* Stay current with GenAI trends, LLM capabilities, AI safety practices, emerging tools, enterprise adoption patterns, and responsible AI guidance.

## Required Qualifications

* Experience designing, developing, or implementing Generative AI, Large Language Model, machine learning, or data-driven solutions.
* Strong understanding of LLM capabilities, limitations, prompting strategies, embeddings, retrieval-augmented generation, fine-tuning, agents, and model evaluation.
* Experience working with technical teams such as Data Science, Machine Learning, Platform Engineering, Software Engineering, or Data Engineering.
* Ability to translate business needs into practical AI solution designs and implementation plans.
* Experience developing AI-powered applications, prototypes, proof-of-concepts, or production-ready AI systems.
* Familiarity with cloud platforms, APIs, data pipelines, model deployment, and enterprise technology environments.
* Understanding of MLOps, LLMOps, model monitoring, evaluation workflows, and production AI lifecycle management.
* Strong analytical, problem-solving, and communication skills.
* Ability to work with clients, gather requirements, explain technical tradeoffs, and guide stakeholders toward practical decisions.
* Strong documentation skills and ability to clearly communicate architecture, assumptions, risks, and recommendations.
* Ability to manage multiple priorities and work effectively in a consulting or client-facing environment.

## Preferred Qualifications

* Experience in management consulting, technology consulting, AI advisory, data consulting, or client-facing solution delivery.
* Hands-on experience with OpenAI, Anthropic, Google Gemini, Azure AI, AWS Bedrock, Hugging Face, Cohere, Mistral, Meta Llama, or similar AI platforms and model providers.
* Experience with GenAI frameworks or orchestration tools such as LangChain, LlamaIndex, Semantic Kernel, Haystack, CrewAI, AutoGen, or similar tools.
* Experience with vector databases or search systems such as Pinecone, Weaviate, Chroma, Milvus, Qdrant, Elasticsearch, OpenSearch, pgvector, or similar technologies.
* Experience implementing retrieval-augmented generation systems, enterprise knowledge assistants, document intelligence tools, agent workflows, or AI-powered automation.
* Familiarity with Python, SQL, APIs, JSON, data processing, cloud services, and modern software development practices.
* Experience with model benchmarking, prompt evaluation, hallucination testing, relevance scoring, safety testing, and output validation.
* Understanding of responsible AI, AI governance, data privacy, model risk management, security, and compliance considerations.
* Experience supporting AI solutions in industries such as financial services, healthcare, life sciences, retail, energy, insurance, technology, or public sector organizations.
* Advanced degree or relevant certification in computer science, data science, artificial intelligence, machine learning, analytics, engineering, or a related field.

## Ideal Candidate Profile

The ideal candidate is a practical and strategic AI consultant who can help clients move from curiosity about Generative AI to real implementation. This person understands both the technical side of GenAI and the business side of adoption, including use case selection, value measurement, stakeholder alignment, risk management, and production readiness.

They should be comfortable discussing high-level AI strategy with executives and then working with technical teams to design architecture, evaluate models, build prototypes, and support deployment. The right candidate will be able to explain when to use RAG, when to consider fine-tuning, when agent workflows are appropriate, and how to validate that a GenAI solution is producing reliable and useful results.

This person should be curious, structured, client-focused, and comfortable operating in fast-changing AI environments. They should bring sound judgment, strong communication skills, and a practical mindset focused on business-centered AI value.

## Work Environment

This role is part of Sia’s AI & Data Business Unit and may involve working with clients across multiple industries. The Generative AI Consultant should be comfortable operating in a consulting environment, participating in client meetings, leading workshops, collaborating with technical teams, and supporting multiple stages of AI solution delivery.

The position may require collaboration across distributed teams and may include work with client stakeholders, data science teams, machine learning engineers, platform engineers, product leaders, and business sponsors. The role requires professionalism, adaptability, strong communication, and the ability to deliver high-quality work in dynamic client environments.

## Compensation and Benefits

Compensation will be based on experience, qualifications, location, and overall fit for the role. Benefits may include:

* Competitive salary
* Full-time employment
* Health, dental, and vision benefits
* Paid time off
* Retirement plan options
* Professional development opportunities
* Exposure to leading AI and data transformation initiatives
* Opportunity to work with clients across multiple industries
* Collaborative consulting environment
* Opportunity to help shape enterprise adoption of Generative AI

## Equal Opportunity Statement

Sia is an equal opportunity employer and welcomes applicants from all backgrounds. Employment decisions are based on qualifications, experience, skills, and business needs. The company is committed to maintaining a respectful, inclusive, and collaborative work environment.