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About This Role
locations
North Carolina, USA
Georgia, USA
Massachusetts, USA
time type
Full time
posted on
Posted Today
job requisition id
JR110980
Genesys empowers organizations of all sizes to improve loyalty and business outcomes by creating the best experiences for their customers and employees. Through Genesys Cloud, the AI\-powered Experience Orchestration platform, organizations can accelerate growth by delivering empathetic, personalized experiences at scale to drive customer loyalty, workforce engagement, efficiency and operational improvements.
We employ more than 6,000 people across the globe who embrace empathy and cultivate collaboration to succeed. And, while we offer great benefits and perks like larger tech companies, our employees have the independence to make a larger impact on the company and take ownership of their work. Join the team and create the future of customer experience together.
Summary:
The SS\&AI (Self Service and Artificial Intelligence) Team is a Professional Services team responsible for the design, development and testing of highly customized Self\-service IVR and AI driven Bot applications (Virtual Agents), generative AI bots and Agentic Virtual Agents across all Genesys platforms.
In this role, candidate will get exciting opportunities to work on latest AI technologies to provide top class CX using inhouse Genesys bots as well as – Google, Amazon, and others. Services provided by the candidate will include software development and Architecture design, Integration consulting, Agile leadership, customer training, team education and owning end to end delivery.
Key Responsibilities:
In this role, the primary responsibilities will include (but are not limited to):
- Responsible for managing project initiatives of strategic importance to the organization.
- Participate in customer workshops and design call flows using our products using design best practices and awareness of product nuances.
- Work Independently, and with Genesys technical teams and business partners, to design, develop and maintain IVR’s, NLU Intent\-based Bots and routing applications for DTMF and speech interactions, Virtual Agents, and Agentic Virtual Agents.
- Experience defining ASR grammars, and tuning process.
- Create accurate development effort estimates in collaboration with the team manager, Professional Services project managers or regional managers.
- Works on significant and unique issues where analysis of situations or data requires an evaluation of broadly defined variables. Requires conceptual thinking to understand advanced issues and implications. Exercises independent judgment in methods, techniques and evaluation criteria for obtaining results. Accountable for results, which may impact their entire function or geography.
- Work with Product owner, Scrum master to drive user story creation and ownership for SS\&AI owned epics for IVR, Routing and bots. Lead the SS\&AI team delivery.
- Present and demonstrate proposed IVR solutions as required. Perform knowledge transfer of the delivered solutions at the conclusion of the engagement as necessary.
- Create and execute test scripts for call flow and other logic and leverage existing Genesys tools (logs, reporting) to provide UAT and QA support.
- Communicate within the global community respecting cultural, language and time zone variations.
- Demonstrate flexibility to adjust working hours to match customer and team interactions.
- Work as a team player to the organization. Providing feedback to the product organization about issues found in API’s, product, documentation or architectures.
- Work independently to provide customer technical consulting services to help drive the determination of key deliverables, outcomes, code best practices, and deployments.
Minimum Requirements:
- BS/MS/BA or equivalent in Computer Science, Engineering or related field preferred.
- 10 \+ Years of experience with commercial IVR applications, Routing, Bots and development experience in appropriate development tools, Advanced Speech Recognition engines. Additional computer languages such as PHP, Java or C\# is a plus.
- 5\+ Years of experience working with voice (and/or digital) bots on platforms like Google Dialogflow and Amazon Lex. Must include webhook/fulfillment experience and development skills.
- Demonstrated Understanding of and experience with the effective use of Generative and Agentic AI tools.
- Demonstrated experience in a customer facing role and handled difficult customer situations and being a thought leader for effective client consulting.
- Understanding of the IVR application architecture including web components, telephony, caching, prompt servers, ASR and operational diagnostics.
- Ability to work independently on routine duties or projects with general instructions on new assignments. Ability to take initiative and help define and create new product features.
- Excellent verbal, writing skills and the ability to effectively interact with clients (business and technical audiences).
Desirable Skills:
- Practical experience developing and deploying Genesys solutions with Genesys tools such as Genesys Cloud, Architect, Dialog Engine, Composer, Designer and Intelligent Automation. Experience with Google Dialog flow and Amazon Lex.
- Genesys GCP or AWS certification.
- Bot and intent tuning.
*\#LI\-REMOTE*
Compensation:
This role has a market\-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate’s experience, qualifications, skills, and location. This role might also be eligible for a commission or performance\-based bonus opportunities.
$110,600\.00 \- $194,400\.00Benefits:
- Medical, Dental, and Vision Insurance.
- Telehealth coverage
- Flexible work schedules and work from home opportunities
- Development and career growth opportunities
- Open Time Off in addition to 10 paid holidays
- 401(k) matching program
- Adoption Assistance
- Fertility treatments
Click here to view a summary overview of our Benefits.
If a Genesys employee referred you, please use the link they sent you to apply.
About Genesys:
Genesys® empowers more than 8,000 organizations worldwide to create the best customer and employee experiences. With agentic AI at its core, Genesys Cloud™ is the AI\-Powered Experience Orchestration platform that connects people, systems, data and AI across the enterprise. As a result, organizations can drive customer loyalty, growth and retention while increasing operational efficiency and teamwork across human and AI workforces. To learn more, visit www.genesys.com.
Reasonable Accommodations:
If you require a reasonable accommodation to complete any part of the application process, or are limited in your ability to access or use this online application and need an alternative method for applying, you or someone you know may contact us at [email protected].
You can expect a response within 24–48 hours. To help us provide the best support, click the email link above to open a pre\-filled message and complete the requested information before sending. If you have any questions, please include them in your email.
This email is intended to support job seekers requesting accommodations. Messages unrelated to accommodation—such as application follow\-ups or resume submissions—may not receive a response.
Genesys is an equal opportunity employer committed to fairness in the workplace. We evaluate qualified applicants without regard to race, color, age, religion, sex, sexual orientation, gender identity or expression, marital status, domestic partner status, national origin, genetics, disability, military and veteran status, and other protected characteristics.
*Please note that recruiters will never ask for sensitive personal or financial information during the application phase.*
Salary Context
This $110K-$194K range is below the median for AI/ML Engineer roles in our dataset (median: $181K across 1996 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,824 AI roles we're tracking, AI/ML Engineer positions make up 71% of the market. At Genesys, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $178,940 based on 11,900 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($152K) sits 15% below the category median. Disclosed range: $110K to $194K.
Across all AI roles, the market median is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $97,380; Mid: $160,000; Senior: $227,400; Director: $243,000; VP: $250,000.
Genesys AI Hiring
Genesys has 4 open AI roles right now. They're hiring across AI/ML Engineer. Positions span NC, US, IN, US, CA, US. Compensation range: $194K - $407K.
Location Context
Across all AI roles, 16% (613 positions) offer remote work, while 3,187 require on-site attendance. Top AI hiring metros: New York (2,448 roles, $210,000 median); San Francisco (1,990 roles, $253,000 median); Los Angeles (1,686 roles, $189,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 3,824 open positions tracked in our dataset. By seniority: 119 entry-level, 1,813 mid-level, 1,472 senior, and 420 leadership roles (Director, VP, C-Level). Remote roles make up 16% of the market (613 positions). The remaining 3,187 roles require on-site or hybrid attendance.
The market median for AI roles is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($293,500 median, 31 roles); AI Safety ($274,200 median, 51 roles); Research Engineer ($260,000 median, 401 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 3,824 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,702), Data Scientist (281), AI Software Engineer (258). 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 (119) are outnumbered by mid-level (1,813) and senior (1,472) 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 420 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 16% of all AI roles (613 positions), with 3,187 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 $200,000. Top-quartile roles start at $253,000, 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $142,800. 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 (1,968 postings), Aws (1,203 postings), Azure (882 postings), Rag (877 postings), Gcp (735 postings), Prompt Engineering (587 postings), Pytorch (586 postings), Claude (554 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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