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Genai Developer Jobs (NOW HIRING)

GenAI Developer

Mclean, VA

$51.50 - $71/hr

... skilled GenAI Engineer to join its technology team in McLean, VA. In this individual contributor role, you will focus on the day-to-day development and implementation of AI-powered solutions.

Senior Java / GenAI Developer Location: Austin, TX or Dallas/ Southlake, TX (Hybrid, 4 days a week onsite) Duration: 12 plus months - CTH Pay rate: $85.00 W2 - Depends on Experience Client: Charles ...

Senior Java / GenAI Developer Location: Austin, TX or Dallas/ Southlake, TX (Hybrid, 4 days a week onsite) Duration: 12 plus months - CTH Pay rate: $85.00 W2 - Depends on Experience Client: Charles ...

Job Summary : LTM is a company specializing in advanced technology solutions, and they are seeking a GenAI Developer. The role involves leading the development of production-ready systems ...

GenAI DevOps Program Manager

Austin, TX · Hybrid

$52.25 - $71.50/hr

NXP is seeking a GenAI DevOps Program Manager that willoversee the strategy, development and deployment of generative AI (GenAI) technologies, ensuring they are integrated efficiently and securely ...

Python GenAI Developer

Tampa, FL · On-site

$47.50 - $65.50/hr

Strong expertise in Natural Language Processing (NLP) and Generative AI (GenAI). * Proficiency with Python frameworks such as Django and Flask. * Extensive experience with machine learning libraries ...

Senior GenAI Engineer (Python)

Palo Alto, CA · On-site

$142K - $192K/yr

As a Senior GenAI Developer, you will lead the design, development, and deployment of scalable GenAI applications that redefine how professional services are delivered. Key Responsibilities: * GenAI ...

Senior GenAI Engineer (Python)

Palo Alto, CA · Hybrid

$143K - $192K/yr

As a Senior GenAI Developer, you will lead the design, development, and deployment of scalable GenAI applications that redefine how professional services are delivered. Key Responsibilities: * GenAI ...

Senior GenAI Engineer (Python)

Palo Alto, CA · Hybrid

$142K - $192K/yr

As a Senior GenAI Developer, you will lead the design, development, and deployment of scalable GenAI applications that redefine how professional services are delivered. Key Responsibilities: * GenAI ...

GEN AI Developer@ Alpharetta, GA

Alpharetta, GA · On-site

$49 - $67.50/hr

GenAI Developer (2 Roles) Location : Alpharetta, GA Hybrid - 3 Days work from office Face to Face is Required. Major Skills - Hands on Python Development, GEN AI Tools, Experience with LangChain and ...

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Genai Developer information

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How much do genai developer jobs pay per hour?

As of Jun 21, 2026, the average hourly pay for genai developer in the United States is $52.84, according to ZipRecruiter salary data. Most workers in this role earn between $40.38 and $64.66 per hour, depending on experience, location, and employer.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior AI researcher, machine learning director, or AI solutions architect, often requiring advanced skills in programming, data analysis, and deep learning. These roles usually involve leadership responsibilities, specialized expertise, and may require relevant certifications or advanced degrees. Compensation at this level reflects significant experience and impact within the organization or industry.

What engineers make $500,000?

Senior engineers in high-demand fields such as software engineering, data engineering, and specialized roles like AI or machine learning engineers can earn $500,000 or more annually, especially with experience, advanced skills, and in competitive industries. Compensation often includes base salary, bonuses, and stock options, particularly at large tech companies or startups with significant funding.

What are some common challenges GenAI Developers face when integrating generative AI models into existing products?

GenAI Developers often encounter challenges related to model deployment, scalability, and ensuring data privacy when integrating generative AI models into established products. Balancing the computational requirements of large AI models with real-time application demands can be complex, and optimizing inference speed without sacrificing model quality is a key consideration. Additionally, collaborating closely with product managers, data scientists, and DevOps teams is essential to align AI outputs with business goals and maintain robust, ethical AI practices.

What jobs pay $2000 a day?

High-paying jobs that can earn $2000 or more per day often include specialized roles such as senior software engineers, data scientists, AI developers, management consultants, and certain medical specialists. These positions typically require advanced skills, extensive experience, and often involve project-based or consulting work with high hourly or daily rates.

What are GenAI Developers?

GenAI Developers are professionals who design, build, and optimize applications using generative artificial intelligence technologies. They work with models such as GPT, DALL-E, or Stable Diffusion to create tools for generating text, images, code, and other content. These developers need strong programming skills, a solid understanding of machine learning, and experience working with AI frameworks and APIs. Their responsibilities often include training custom models, integrating AI into products, and ensuring ethical use of generative AI solutions.

What are the key skills and qualifications needed to thrive as a GenAI Developer, and why are they important?

To thrive as a GenAI Developer, you need a strong background in machine learning, deep learning frameworks (like TensorFlow or PyTorch), and programming languages such as Python, often supported by a degree in computer science or a related field. Familiarity with cloud platforms (AWS, Azure, GCP), APIs, and prompt engineering, as well as certifications in AI or ML, are typically used in this role. Creativity, problem-solving, and effective communication set outstanding GenAI Developers apart. These skills are crucial for building, optimizing, and deploying powerful generative AI models that address complex business challenges.

What is the difference between Genai Developer vs Machine Learning Engineer?

AspectGenai DeveloperMachine Learning Engineer
Required CredentialsBachelor's in CS, AI, or related; experience with NLP and AI frameworksBachelor's or higher in CS, Data Science, or related; strong programming and ML skills
Work EnvironmentDevelops AI models focused on generative AI, often in AI startups or tech companiesBuilds and deploys ML models across various industries, including tech, finance, healthcare
Employer & Industry UsagePrimarily in AI-focused companies, research labs, and tech firmsWidely used across industries like tech, finance, healthcare, and retail

While both roles involve AI and machine learning, Genai Developers specialize in creating generative AI models like chatbots and content generators, whereas Machine Learning Engineers develop a broader range of ML models for various applications. The roles overlap in skills and tools but differ in focus and industry applications.

What is the salary of GenAI developer?

The salary of a GenAI developer typically ranges from $80,000 to $150,000 annually, depending on experience, location, and skill set. Senior roles or those with expertise in machine learning frameworks and large language models may earn higher compensation. Salaries can also vary based on industry and company size.
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$51.50 - $71/hr

Other

Posted 23 days ago


Job description

Location

McLean, VA (On-site / Hybrid)

Role Type

Individual Contributor Developer

Employment

Contract / Full-Time

Primary Skills

Python RAG MCP AI Agents

About the Role

Client is seeking a skilled GenAI Engineer to join its technology team in McLean, VA. In this individual contributor role, you will focus on the day-to-day development and implementation of AI-powered solutions. Architecture and system design decisions are handled by the client's senior architecture team - your mandate is to build, integrate, test, and iterate on AI features at pace. If you are a strong Python developer with hands-on experience in RAG pipelines and modern AI tooling, this is your opportunity to work on impactful solutions at one of the nation's leading mortgage enterprises.

Key Responsibilities

  • Develop, test, and maintain AI/ML features and integrations as directed by the architecture team.
  • Build and optimize Retrieval-Augmented Generation (RAG) pipelines for enterprise knowledge retrieval use cases.
  • Implement and integrate Model Context Protocol (MCP) servers and clients to extend AI model capabilities.
  • Write clean, well-documented Python code following established coding standards and best practices.
  • Integrate AI components with existing internal systems, APIs, and data sources.
  • Collaborate with architects, product owners, and business stakeholders to translate requirements into working solutions.
  • Participate in code reviews, testing, and QA cycles to ensure reliability and performance.
  • Monitor, debug, and iterate on deployed AI features based on performance metrics and user feedback.
  • Maintain technical documentation for developed components and integrations.
  • Stay current with the rapidly evolving AI/LLM tooling landscape and propose improvements where applicable.

Required Qualifications

  • Strong proficiency in Python for backend and AI/ML development.
  • Experience working with REST APIs, message queues, and cloud-based infrastructure.
  • Familiarity with version control (Git) and CI/CD workflows.
  • Hands-on experience building and deploying RAG (Retrieval-Augmented Generation) pipelines, including chunking strategies, embedding models, and vector stores.
  • Working knowledge of Model Context Protocol (MCP) - building or consuming MCP servers/clients to connect LLMs to external tools and data.
  • Experience with at least one major LLM provider API (OpenAI, Anthropic, Azure OpenAI, etc.) for inference and prompt engineering.
  • Familiarity with vector databases such as Chroma, Pinecone, Weaviate, pgvector, or equivalent.
  • Experience building scalable, production-grade AI agents using frameworks such as LangGraph, CrewAI, AutoGen, or custom orchestration layers.
  • Familiarity with agentic design patterns: tool use, memory management, multi-step reasoning, and human-in-the-loop workflows.
  • Background in financial services, mortgage, or regulated industry environments.
  • Experience with LLM observability and evaluation tools (e.g., LangSmith, Phoenix, RAGAS).
  • Knowledge of containerization and deployment (Docker, Kubernetes).