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About This Role
Summary
Evolutio is at the forefront of the rapidly-growing Data Science and AI sector, delivering value for our clients across diverse industries. As an AI Consultant, you will be driving success in our Data Science and AI professional services practice.
In your capacity as an AI Consultant you will drive profitability by dedicating 75% of your time to billable client work, providing technical expertise and hands-on data science services. This aspect of the role demands deep technical expertise in AI and data science, allowing you to lead by example in the delivery of
sophisticated AI solutions. Your contributions will directly impact our clients, delivering value through innovative data science practices and reinforcing our reputation for excellence in professional service delivery.
Details
department
Engineering Services
employment type
Full time
location
Remote (US)
experience
Software development and architecture experience across cloud environments (GCP, AWS, Azure) and familiarity with various AI platforms and tools
Responsibilities
- Collaborate with clients to design and develop AI-powered solutions that solve real business problems and align with user needs
- Contribute to the technical design and development of machine learning models, ensuring high performance and accuracy
- Lead the development and execution of scalable and repeatable solutions for clients
- Apply a wide range of machine learning techniques including classification, regression, time-series forecasting, Visual AI, and Generative AI
- Work hands-on in designing, building, and validating models using industry-standard frameworks and tools
- Support the delivery of end-to-end data science workflows, from data preparation through model deployment
- Work with clients to develop and deliver use cases that include leveraging LLMs to summarize and automate parts of a process
- Promote knowledge sharing and help elevate the overall technical acumen of the delivery team
- Identify impactful use cases for AI/ML across various industries and help prototype and validate solutions
- Work closely with stakeholders to understand business requirements and contribute to high-impact, client-facing proposals
- Help drive project delivery by translating technical solutions into clear, actionable plans and deliverables
- Maintain strong client relationships through responsive communication and consistent delivery
- Gather and incorporate client feedback throughout development cycles to improve solution quality and user satisfaction
- Support the release process from MVP to production, balancing agility with stability and quality assurance
Qualifications and requirements
- Bachelor's degree in Computer Science, Engineering, a related field, or 4 years relevant work experience
- 4 years of experience in a technical engineering role
- 2 years of experience in Saas development or technical consulting
- Demonstrated expertise in data science, machine learning, and AI including proficiency in SQL, Python Software Development, Machine Learning Model Development, and AI Observability
- Demonstrated expertise in Data Engineering, Data Warehousing, and Data Visualization including Kafka, Spark, DataBricks, Snowflake, Tableau, and PowerBI
- Proven enterprise client management experience with exceptional written and verbal communication skills, able to act as the bridge between technical and non-technical audiences
Preferred skills and experience
- SnowPro Core Certification
- Software development and architecture experience across cloud environments (GCP, AWS, Azure) and familiarity with various AI platforms and tools
- Experience in product management, including Agile and Scrum methodologies
- Possess a high level of motivation and self-direction, coupled with an entrepreneurial drive
- Outstanding skills in building relationships, with a track record of developing mutually beneficial partnerships
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Essentials
- Medical, dental, vision coverage;
- 10 days PTO, to use whenever;
- Additional company-wide PTO for company holidays including New Year Holiday (1-week), Independence Day Holiday (1-week), Martin Luther King Jr Day, Memorial Day, Labor Day, Thanksgiving Holiday (2-days);
- Generous paid leave after becoming a parent;
- Volunteer opportunities for our "Engineering for Good" projects
Benefits
- Enjoy Great Compensation & Benefits: Healthcare, vacation package, time off for the holidays and summertime to name a few. In 2021 we flew our entire company and a guest to South Africa to work on our "Engineering for Good" projects.
- Solve Fascinating Customer Problems: We work with some of the biggest brands on the planet. Get under-the-hood with Fortune 1,000 customers and the leading partner technologies in the space. We're going fast, so bring your creativity to help us mold the clay.
- Get Career Development and Growth: We merge business with information technology, and we'll teach our colleagues from consultants and salespeople how to think like a technical leader with 1:1 coaching, shadowing, and certifications.
- Work With a Diverse, Creative, Talented Team: We empower our people to make decisions to do their best work, which is much easier when the vision is communicated clearly. We're a team that's proud of our colleagues, which is fueled by creative, inclusive, and energized individuals.
In the Industry
- Work with the most disruptive, cutting edge technologies in the market;
- We are an AppDynamics Elite Partner, which is the highest partner level; and
- Evolutio is part of the Group Elephant company ecosystem, meaning there are opportunities to work with partners and customers across the globe.
Role Details
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 9,653 AI roles we're tracking, AI Consultant positions make up 0% of the market. At evolutio, 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
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 $148,848 based on 19 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
evolutio AI Hiring
evolutio has 1 open AI role right now. They're hiring across AI Consultant. Based in Remote, US.
Remote Work Context
Remote AI roles pay a median of $185,906 across 2,124 positions. About 6% of all AI roles offer remote work.
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 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). 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 (193) are outnumbered by mid-level (4,500) and senior (3,455) 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 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 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 $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. 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 Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. 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: Python (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 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
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