Generative AI Consultant

$94K - $114K New York, NY, US Mid Level AI Consultant

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Skills & Technologies

AnthropicAutogenAwsAzureChromaClaudeDockerEmbeddingsGcpGemini

About This Role

Company Description About Sia

Sia is a next\-generation, global management consulting group. Founded in 1999, we were born digital. Today our strategy and management capabilities are augmented by data science, enhanced by creativity and driven by responsibility. We’re optimists for change and we help clients initiate, navigate and benefit from transformation. We believe optimism is a force multiplier, helping clients to mitigate downside and maximize opportunity. With expertise across a broad range of sectors and services, our 3,000 consultants serve clients worldwide from 48 locations in 19 countries. Our expertise delivers results. Our optimism transforms outcomes.

Sia’s AI \& Data Business Unit is the powerhouse of our firm’s innovation—merging cutting\-edge Data Science, Generative AI, and advanced digital solutions to transform industries. With over 350 experts worldwide, we tackle projects from proof\-of\-concept to large\-scale deployment, always pushing the boundaries of AI capabilities. Our 12 R\&D labs in Europe and North America drive continuous research in areas like computer vision, MLOps, and deep learning, partnering closely with our business consultants for real\-world impact. By joining Sia’s AI \& Data team, you’ll step into a vibrant, collaborative environment that nurtures professional growth and empowers you to shape the future of AI\-driven consulting.

Job Description

Join us as an experienced Generative AI Specialist designing and implementing cutting\-edge GenAI/LLM solutions across diverse industries. You'll act as a vital bridge between technical teams (Data Science, ML, Platform) to deliver business\-centric AI value. You'll guide clients on the optimal path—using techniques like RAG, agents, or fine\-tuning—for cost\-effective impact.

Your responsibilities extend beyond prompting to architecting robust AI products via benchmarking, prototyping, and validation. You'll orchestrate the full AI workflow, ensuring seamless model integration optimized for performance, security, and scale, while tackling infrastructure challenges. We provide extensive training to support your success. If you're driven to push AI boundaries and help clients rapidly adopt GenAI with confidence, apply to make a real difference.

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).

Qualifications Education:

  • Master's degree or Engineering degree (or equivalent) in Computer Science, Engineering, Data Science, or a related quantitative field.
  • Experience: 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.

Required Technical Skills:

  • Strong programming skills, particularly in Python.
  • Proficiency in at least one major GenAI application framework (LangChain, LlamaIndex, etc.).
  • 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.

Soft Skills:

  • Excellent communication skills (written and verbal), ability to explain complex technical concepts simply.
  • Strong analytical and complex problem\-solving abilities.
  • Team player with the ability to collaborate effectively with diverse profiles.
  • Curiosity, pioneering spirit, and a demonstrated commitment to continuous learning.

Preferred Qualifications:

  • Experience building agentic AI systems (e.g., LangGraph, AutoGen).
  • Experience with vector databases (e.g., pgvector, Pinecone, Chroma, OpenSearch).
  • Experience developing conversational AI systems / chatbots.
  • Familiarity with deep learning frameworks (PyTorch, TensorFlow).
  • Understanding of or experience with protocols and standards for connecting LLMs to external tools and databases, such as Model Context Protocol (MCP).
  • Experience deploying models at scale in production environments.

Additional Information Compensation \& Benefits

  • Salary range is between $94,000\.00 and $114,000\.00 annually \+ Annual Discretionary Bonus
  • Healthcare coverage that includes 3 medical plan options: Anthem – EPO HSA, EPO HSA MERP, and PPO; dental and vision through MetLife; and life insurance policies through Mutual of Omaha
  • Flexible Spending Account (FSA)
  • Paid Time Off
  • Parental leave paid at 100% of base pay for all new parents
  • 9 Company Holidays \+ 1 Floating Holiday
  • 401(k) Plan \- 4% matching and vested on day 1
  • College save\-up plan \& college loan repayment plan
  • Monthly cell phone stipend
  • Pre\-tax account for Parking and Mass Transit
  • Sia provides several wellness and incentive programs free of charge through the firm medical plan – Anthem \- such as:

+ Gym Reimbursement

+ LiveHealth Online

+ Well\-being Coach

+ Building Healthy Families Program

+ And much more

Diversity, Equity, Inclusion \& Belonging

At Sia, we believe in fostering a diverse, equitable and inclusive culture where our employees and partners are valued and thrive in a sense of belonging. We are committed to recruiting and developing a diverse network of employees and investing in their growth by providing unique opportunities for professional and cultural immersion. Our commitment toward inclusion motivates dynamic collaboration with our clients, building trust by creating an inclusive environment of curiosity and learning which affects lasting impact. Please visit our website for more information.

Sia is an equal opportunity employer. All aspects of employment, including hiring, promotion, remuneration, or discipline, are based solely on performance, competence, conduct, or business needs.

Office Workplace Guidelines

Sia is committed to providing a flexible workplace environment that supports client, business, and market needs. Consultants located in our primary market office locations—New York City, Charlotte, Seattle, and San Francisco—are expected to live within a reasonable commuting distance and attend the office at least three days per week. For Consultants outside of our primary markets, we can offer more flexible in\-person requirements in accordance with your location.

Work Authorization \& Sponsorship

At this time, Sia does not intend to pursue employment with applicants who will require now or in the future visa by our company for work authorization in the United States (i.e., H1\-B visa, F\-1 visa (OPT), TN visa, or any other non\-immigrant status).

Sia is an equal opportunity employer. All aspects of employment, including hiring, promotion, remuneration, or discipline, are based solely on performance, competence, conduct, or business needs.

Salary Context

This $94K-$114K range is in the lower quartile for AI Consultant roles in our dataset (median: $136K across 49 roles with salary data).

Role Details

Company SIA
Title Generative AI Consultant
Location New York, NY, US
Category AI Consultant
Experience Mid Level
Salary $94K - $114K
Remote No

About This Role

This role sits at the intersection of AI and engineering, building systems that bring machine learning capabilities into production environments. The scope varies by company, but the common thread is applying AI technology to solve real business problems at scale. Most AI roles today require a combination of software engineering fundamentals and domain-specific ML knowledge, with the exact mix depending on the team's maturity and the product they're building.

The AI job market is evolving fast. New role categories emerge as companies figure out what they need to ship AI-powered products. What matters most is the ability to learn quickly, build working systems, and iterate based on real-world performance data. The specific title matters less than the skills you bring and the problems you can solve. Companies are past the experimentation phase and want engineers who can deliver production-quality systems that work reliably at scale.

Across the 26,159 AI roles we're tracking, AI Consultant positions make up 0% of the market. At SIA, this role fits into their broader AI and engineering organization.

AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.

What the Work Looks Like

Day-to-day work involves a mix of building, debugging, and collaborating. You'll write code, review pull requests, participate in design discussions, and work with cross-functional teams (product, design, data) to define what AI features should do and how they should behave. Expect to spend time on both technical implementation and communication. Most AI teams operate in two-week sprint cycles, with regular demos and retrospectives. The ratio of heads-down coding to meetings and reviews varies by seniority, with senior roles spending more time on architecture decisions and mentorship.

AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.

Skills Required

Anthropic (3% of roles) Autogen (1% of roles) Aws (34% of roles) Azure (10% of roles) Chroma Claude (5% of roles) Docker (4% of roles) Embeddings (2% of roles) Gcp (9% of roles) Gemini (4% of roles)

Python and cloud platform experience are common requirements. Specific skill needs vary by company and focus area, but familiarity with ML frameworks, data pipelines, and API design covers the basics for most roles. RAG (Retrieval-Augmented Generation), vector databases, and LLM API integration are increasingly standard requirements across role types.

Beyond the core stack, communication skills matter more than many technical candidates realize. The ability to explain AI capabilities and limitations to non-technical stakeholders is a differentiator at every level. Technical writing, documentation, and clear thinking about tradeoffs are underrated skills in AI roles. Experience with evaluation methodology (how to measure whether an AI system is working well) is becoming a core requirement, especially for roles that involve LLM integration.

Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.

Compensation Benchmarks

AI Consultant roles pay a median of $205,800 based on 51 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $131,300. This role's midpoint ($104K) sits 49% below the category median. Disclosed range: $94K to $114K.

Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.

SIA AI Hiring

SIA has 3 open AI roles right now. They're hiring across AI Consultant, AI/ML Engineer. Based in New York, NY, US. Compensation range: $114K - $250K.

Location Context

AI roles in New York pay a median of $200,000 across 1,670 tracked positions. That's 9% above the national median.

Career Path

Common paths into AI Consultant roles include Software Engineer, Data Scientist, Data Analyst.

From here, career progression typically leads toward Senior Engineer, AI Architect, Engineering Manager, Principal Engineer.

Focus on building things that work. A deployed project that solves a real problem is worth more than any certification. Contribute to open-source, build portfolio projects, and invest in fundamentals (software engineering, statistics, systems design) rather than chasing the latest framework. The AI field moves fast, but the engineers who succeed long-term are the ones with strong fundamentals who can adapt to new tools and paradigms as they emerge.

What to Expect in Interviews

AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.

When evaluating opportunities: Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.

AI Hiring Overview

The AI job market has 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.

The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 roles).

AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.

The AI Job Market Today

The AI job market spans 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.

The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (2,416) are outnumbered by mid-level (16,247) and senior (5,153) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 2,343 positions, representing the bottleneck between technical execution and organizational strategy.

Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.

AI compensation is structured in clear tiers. The market median sits at $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.

Category matters for compensation. AI Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.

The most in-demand skills across all AI postings: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.

Frequently Asked Questions

Based on 51 roles with disclosed compensation, the median salary for AI Consultant positions is $205,800. Actual compensation varies by seniority, location, and company stage.
Python and cloud platform experience are common requirements. Specific skill needs vary by company and focus area, but familiarity with ML frameworks, data pipelines, and API design covers the basics for most roles. RAG (Retrieval-Augmented Generation), vector databases, and LLM API integration are increasingly standard requirements across role types.
About 7% of the 26,159 AI roles we track offer remote work. Remote availability varies by company and seniority level, with senior and leadership roles more likely to offer location flexibility.
SIA is among the companies actively hiring for AI and ML talent. Check our company profiles for detailed breakdowns of open roles, salary ranges, and hiring trends.
Common next steps from AI Consultant positions include Senior Engineer, AI Architect, Engineering Manager, Principal Engineer. Progression depends on whether you lean toward technical depth, people management, or product strategy.

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