GenAI Engineer

PhoenixTeam

GenAI Engineer designing, deploying, and scaling generative AI solutions for real business use cases at PhoenixTeam. Collaborating with stakeholders to transform AI concepts into production-ready solutions.

Posted 7/25/2026full-timeRemote • Virginia • 🇺🇸 United StatesMid-LevelSenior💰 $60,000 - $130,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying generative AI and machine learning solutions, with a strong focus on translating business requirements into scalable architectures. Proficient in MLOps practices and effective communication with both technical and non-technical stakeholders.

Highest-signal resume keywords

Generative AI SolutionsMachine Learning Model DeploymentMLOps PracticesCloud Platforms (AWS, Azure, GCP)Strong Communication Skills

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Generative AIMachine LearningLLMsFine-TuningEmbeddingsAI Evaluation MethodsPerformance MetricsContainerizationModel MonitoringAI/NLP Applications

Soft Skills

OwnershipCollaborationMentoringCommunicationAdaptability

Certifications & Qualifications

Bachelor’s Degree in Computer ScienceMaster’s Degree in AI or Machine Learning

Industry Keywords

Ethical AIData Security PrinciplesAI GovernanceBusiness Use CasesTechnical Stakeholders

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud Platform

About the role

Key responsibilities & impact

Design, implement, fine-tune, and deploy generative AI and ML solutions aligned to real business use cases.
Translate technical and business requirements into scalable AI architectures and implementation plans.
Lead or support end-to-end AI solution delivery, from experimentation through deployment and iteration.
Serve as the primary technical voice on GenAI initiatives, ensuring clarity across technical and non-technical stakeholders.
Evaluate and apply appropriate models (e.g., GPT-based LLMs, BERT-style architectures, or other approaches) based on problem context.
Fine-tune, integrate, and operationalize models with support from specialized teammates when needed.
Contribute to decisions around model performance, cost, latency, and reliability tradeoffs.
Support early MLOps practices, including deployment patterns, monitoring, and iteration.
Partner closely with Value Engineers, product leaders, and clients to align AI solutions with business goals.
Communicate complex technical concepts clearly to non-technical audiences.
Contribute to internal knowledge sharing, patterns, and best practices for GenAI delivery.
Mentor teammates and support PhoenixTeam learning and growth initiatives.
Stay current on emerging GenAI techniques, tools, and platforms.
Experiment with new approaches and bring practical insights back to the team.

Requirements

What you’ll need

Bachelor’s or Master’s degree in Computer Science, AI, Machine Learning, or a related field.
Experience delivering technical projects that involve collaboration across stakeholders with varying technical depth.
Hands-on familiarity with generative AI concepts (e.g., LLMs, fine-tuning, embeddings) and a strong desire to deepen expertise.
Experience deploying or working with models on cloud platforms (AWS, Azure, or GCP).
Strong communication skills – you can explain why and how, not just what.
Ability to take ownership, manage priorities, and deliver outcomes in fast-moving environments.
Exposure to MLOps practices, containerization, or model monitoring (nice-to-have).
Experience with AI/NLP applications beyond basic experimentation (nice-to-have).
Familiarity with AI evaluation methods and performance metrics (nice-to-have).
Interest in ethical AI, governance, and data security principles (nice-to-have).

Benefits

Comp & perks

Health insurance
Paid time off
Professional development opportunities