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About This Role
Role: Sr Staff AI Engineer (AI Advisory, GenAI/AI Agents)
Location: US Remote
Synonymous Business Title (s): *Sr. Manager, AI Advisory*
Overview:
The Sr. Staff AI Engineer is a senior leader within Blue Yonder’s Supply Chain Advisory AI team, responsible for designing, building, and operationalizing advanced AI and machine learning driven solutions that address complex, real world supply chain challenges. This role blends supply chain domain expertise with hands\-on ML and GenAI agent development, to accelerate AI adoption and deliver measurable operational and financial outcomes.
The role partners closely with customers, product, engineering, and advisory teams to translate business problems into scalable AI solutions. This role serves as a trusted expert who can clearly articulate value, guide implementation, and drive sustained adoption across customer environments.
*We are looking for strong candidates with hands\-on architecture and engineering experience, building and deploying AI agents for enterprise customers within a professional services team.*
What You’ll Be Doing:
AI Solution Design, Architecture \& Delivery
- Design, build, and deploy machine learning models across the full solution lifecycle, including data preparation, validation, deployment, and monitoring.
- Architect and develop GenAI‑powered agents, including prompt and context engineering, retrieval‑augmented generation (RAG), multi‑agent orchestration, and integration with ML models and optimization solvers.
- Translate complex customer business problems into AI‑driven predictions and recommendations that deliver measurable outcomes such as cost reduction, service improvement, and revenue uplift.
- Lead and contribute to rapid customer POCs, experiments, and pilots, iterating solutions toward scalable, production‑ready implementations.
Customer Advisory \& Adoption
- Work directly with customers to build trust, demonstrate explainability, and operationalize AI by embedding agents and models into daily workflows.
- Guide customers through adoption and change management, supporting the transition from experimentation to sustained AI‑driven transformation.
- Confidently communicate AI strategy, risks, and value to technical, business, and executive stakeholders.
Engineering \& Platform Integration
- Partner with engineering teams on full‑stack development, including front‑end and back‑end integration, microservices extensions, and CI/CD enablement.
- Ensure AI solutions integrate effectively within enterprise platforms and the Blue Yonder ecosystem, balancing scalability, performance, and cost.
Thought Leadership \& Practice Contribution
- Act as a thought leader within the AI Advisory community, mentoring peers and contributing to best practices and delivery standards.
- Stay current on advancements in ML, GenAI frameworks, and supply chain AI applications, applying new techniques where they provide tangible customer value.
What We’re Looking For:
Required Qualifications:
- 8 years of hands\-on professional experience in data science, machine learning, advanced analytics, AI engineering, data engineering or software engineering within enterprise\-scale environments.
- Strong hands\-on experience with Python, SQL, and modern data engineering practices, including buildable scalable data pipelines, ETL/ELT workflows, data integration processes, and production\-grade analytics or AI/ML solutions.
- Must have demonstrated experience with modern AI/GenAI capabilities, including agent\-based systems, RAG architecture, prompt and context engineering, multi\-agent orchestration, model fine\-tuning, and LLM\-based solution design.
- Strong collaboration skills and ability to operate effectively in ambiguous, complex problem spaces.
Preferred Qualifications:
- Bachelor’s or Advanced Degree (Masters, PHD, etc.) in Data Science, Computer Science, Engineering, or a related field, or equivalent practical experience.
- Familiarity with Snowflake Cortex, semantic layers, Cortex Analyst/Agents, or similar AI\-enabled data platform capabilities is preferred.
- experience with knowledge graphs, ontology\-driven modeling, graph\-based reasoning, and platforms such as Relational AI, Neo4j, or similar technologies to enhance AI agents, RAG workflows, contextual reasoning, explainability, and enterprise decision intelligence.
- Deep supply chain domain expertise across one or more functional areas, including; planning, merchandising, allocation, replenishment, fulfillment, procurement, or returns.
- Experience across at least one industry vertical; Manufacturing, Retail, or Logistics Service Providers (e.g., Automotive, High Tech, Hardlines, Softlines, Grocery).
- Experience acting as a mentor or technical leader within AI or advanced analytics teams.
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*The annual base salary range for this position is USD $150,385* *\- $189,615\.38**.*
The salary range information provided, reflects the anticipated base salary range for this position based on current national data. Minimums and maximums may vary based on location. Individual salary will be commensurate with skills, experience, certifications or licenses and other relevant factors. In addition, this role will be eligible to participate in either the annual performance bonus or commission program, determined by the nature of the position.
At Blue Yonder, we care about the wellbeing of our employees and those most important to them. This is reflected in our robust benefits package and options that includes:
- Comprehensive Medical, Dental and Vision
- 401K with Matching
- Flexible Time Off
- Corporate Fitness Program
- A variety of voluntary benefits such as; Legal Plans, Accident and Hospital Indemnity, Pet Insurance and much more
At Blue Yonder, we are committed to a workplace that genuinely fosters inclusion and belonging in which everyone can share their unique voices and talents in a safe space. We continue to be guided by our core values and are proud of our diverse culture as an equal opportunity employer. We understand that your career search may look different than others, and embrace the professional, personal, educational, and volunteer opportunities through which people gain experience.
Our Values
If you want to know the heart of a company, take a look at their values. Ours unite us. They are what drive our success – and the success of our customers. Does your heart beat like ours? Find out here: Core Values
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.
Salary Context
This $150K-$189K range is below the median for AI Agent Developer roles in our dataset (median: $190K across 44 roles with salary data).
View full AI Agent Developer salary data →Role Details
About This Role
AI Agent Developers build autonomous systems that can reason, plan, and take actions. They design multi-step workflows, tool-use frameworks, and orchestration layers that let LLMs interact with external systems. This is the frontier of applied AI engineering.
Agent development is where the most interesting (and hardest) problems in applied AI live right now. Making an LLM answer a question is straightforward. Making it reliably execute a 15-step workflow that involves calling APIs, reading databases, making decisions, and recovering from errors is an unsolved problem. You're building systems that have to work despite the fact that the underlying model is non-deterministic.
Across the 4,133 AI roles we're tracking, AI Agent Developer positions make up 1% of the market. At Blue Yonder, this role fits into their broader AI and engineering organization.
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
What the Work Looks Like
A typical week includes: designing the action space and tool definitions for a new agent use case, debugging why the agent chose the wrong action sequence on a specific input, building evaluation frameworks that test agent reliability across hundreds of scenarios, optimizing the prompt chain for cost and latency, and implementing safety guardrails to prevent the agent from taking destructive actions. The work is equal parts engineering and empirical science.
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
Skills Required
Deep experience with LLM APIs and agent frameworks (LangChain, CrewAI, AutoGen). Strong understanding of prompt engineering, function calling, and error handling for non-deterministic systems. Python is standard. Experience with orchestration patterns, state management, and workflow engines adds significant value.
The best agent developers think like systems engineers. They design for failure modes, build observability into every step, and understand that agent reliability is the product. Expertise in evaluation methodology for non-deterministic systems is the differentiator. Can you measure whether your agent works 'well enough'? Can you find the edge cases where it breaks?
Look for roles that describe specific agent use cases, mention evaluation methodology, and talk about production deployment. Early-stage companies exploring agents can be exciting, but be prepared for ambiguity. The most valuable roles are at companies that have already shipped a v1 and need to make it reliable.
Compensation Benchmarks
AI Agent Developer roles pay a median of $241,950 based on 112 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($170K) sits 30% below the category median. Disclosed range: $150K to $189K.
Across all AI roles, the market median is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Safety ($274,200) and AI Engineering Manager ($268,700). By seniority level: Entry: $97,760; Mid: $165,778; Senior: $227,400; Director: $250,000; VP: $250,000.
Blue Yonder AI Hiring
Blue Yonder has 1 open AI role right now. They're hiring across AI Agent Developer. Based in Dallas, TX, US. Compensation range: $189K - $189K.
Location Context
Across all AI roles, 14% (583 positions) offer remote work, while 3,532 require on-site attendance. Top AI hiring metros: New York (2,760 roles, $211,000 median); San Francisco (2,258 roles, $253,000 median); Los Angeles (1,841 roles, $195,000 median).
Career Path
Common paths into AI Agent Developer roles include Software Engineer, LLM Engineer, Prompt Engineer.
From here, career progression typically leads toward AI Architect, Principal Engineer, Head of AI Engineering.
Build agents. That's the portfolio. Take an open-source agent framework, build something that completes a non-trivial multi-step task, evaluate it rigorously, and document what you learned about reliability, cost, and failure modes. The field is new enough that practical experience counts for more than credentials.
What to Expect in Interviews
Interviews focus on systems thinking and reliability engineering. Expect questions about agent architecture: how you'd design a multi-step workflow with error recovery, how you'd evaluate agent performance, and how you'd prevent agents from taking destructive actions. Coding exercises often involve building a simple agent with tool use and evaluating its behavior across different scenarios. Discussion of safety and guardrails is increasingly common.
When evaluating opportunities: Look for roles that describe specific agent use cases, mention evaluation methodology, and talk about production deployment. Early-stage companies exploring agents can be exciting, but be prepared for ambiguity. The most valuable roles are at companies that have already shipped a v1 and need to make it reliable.
AI Hiring Overview
The AI job market has 4,133 open positions tracked in our dataset. By seniority: 106 entry-level, 1,901 mid-level, 1,663 senior, and 463 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (583 positions). The remaining 3,532 roles require on-site or hybrid attendance.
The market median for AI roles is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Safety ($274,200 median, 57 roles); AI Engineering Manager ($268,700 median, 42 roles); Research Engineer ($260,000 median, 442 roles).
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
The AI Job Market Today
The AI job market spans 4,133 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,865), Data Scientist (339), AI Software Engineer (313). 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 (106) are outnumbered by mid-level (1,901) and senior (1,663) 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 463 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (583 positions), with 3,532 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 $200,700. Top-quartile roles start at $254,000, and the 90th percentile reaches $307,500. 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 $274,200 median, while Prompt Engineer roles sit at $140,000. 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 (2,128 postings), Aws (1,324 postings), Azure (1,003 postings), Rag (916 postings), Gcp (817 postings), Pytorch (655 postings), Prompt Engineering (639 postings), Claude (571 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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