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Genai Engineer Jobs (NOW HIRING)

... engineering, and context management. • Experience integrating GenAI with Azure OpenAI, AWS Bedrock, Vertex AI, OpenAI, Anthropic, and Gemini, along with enterprise APIs, middleware, and data ...

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 ...

Prompt engineering: Crafting and refining prompts to guide generative models to produce desired ... Experience integrating GenAI models and services into existing applications using APIs \n \n \n \n ...

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 ...

NY · On-site

$120 - $150/hr

The Role As a GenAI Developer (GCP) , you will play a key role in designing, building, and deploying scalable AI-powered applications using Large Language Models and Google Cloud Platform. Working in ...

NY · On-site

$55.40 - $94.96/hr

The organization seeks a GenAI Engineer (AWS and Terraform) to lead the migration and operationalisation of generative AI applications on Amazon Web Services. The person in this role will design and ...

$130K - $170K/yr

We are looking for a GenAI Engineer with strong expertise in LLM infrastructure, model deployment, and high-performance inference services. The ideal candidate will build and manage scalable ...

$104K - $137K/yr

We are looking for a GenAI Engineer with strong expertise in LLM infrastructure, model deployment, and high-performance inference services. The ideal candidate will build and manage scalable ...

Senior Staff GenAI Engineer

Sunnyvale, CA · On-site

$200K - $235K/yr

The Senior Staff GenAI Engineer leads the design, development, and deployment of scalable, reliable generative AI systems, driving agentic automation and integration to deliver highimpact ...

Showing results 41-60

Genai Engineer information

What is a GenAI engineer?

A GenAI Engineer is a professional who specializes in designing, developing, and deploying generative artificial intelligence (AI) models and applications. This role involves working with advanced machine learning techniques, such as large language models and generative adversarial networks, to create systems that can generate text, images, code, or other content. GenAI Engineers collaborate with data scientists, software engineers, and product teams to integrate AI capabilities into products and services, ensuring ethical use and scalability. They also stay updated on the latest developments in AI research to continually improve model performance and effectiveness.

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

To thrive as a GenAI Engineer, you need expertise in machine learning, deep learning, and programming languages such as Python, along with a solid understanding of generative models like GANs and transformers. Familiarity with frameworks such as TensorFlow or PyTorch, and experience with cloud platforms and MLOps tools, are highly valuable; advanced degrees or certifications in AI or data science are often preferred. Strong problem-solving, creativity, and communication skills help GenAI Engineers design innovative solutions and effectively collaborate with multidisciplinary teams. These skills ensure the development of robust, scalable generative AI systems that address complex real-world challenges.

What are some typical challenges a GenAI engineer faces when deploying AI models in production environments?

GenAI Engineers often encounter challenges such as ensuring model scalability, addressing bias in generated outputs, and maintaining performance consistency in real-world applications. Deploying generative AI models requires careful monitoring to prevent unexpected or inappropriate outputs, as well as efficient resource management to handle large-scale computations. Collaborating closely with data engineers, product managers, and ML operations teams is essential to streamline deployment pipelines and quickly resolve issues that arise in live environments.

What is the difference between Genai Engineer vs Data Scientist?

AspectGenai EngineerData Scientist
Required CredentialsDegree in Computer Science, AI, or related fields; experience with AI/ML frameworksDegree in Data Science, Statistics, or related fields; strong programming skills
Work EnvironmentDevelops AI models, fine-tunes generative AI systems, collaborates with AI teamsAnalyzes data, builds predictive models, interprets complex datasets
Employer & Industry UsageTech companies, AI startups, research labs focusing on generative AIFinance, healthcare, marketing, and tech firms analyzing data for insights

While both roles require strong technical skills and a background in data or AI, Genai Engineers focus on developing and deploying generative AI models, whereas Data Scientists analyze data to extract insights and build predictive models. The roles often overlap but serve different primary functions within AI and data-driven organizations.

More about Genai Engineer jobs

What cities are hiring for Genai Engineer jobs?

Cities with the most Genai Engineer job openings:

What states have the most Genai Engineer jobs?

States with the most job openings for Genai Engineer jobs include:

Infographic showing various Genai Engineer job openings in the United States as of August 2026, with employment types broken down into 93% Full Time, 3% Part Time, and 4% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution.

Full-time

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Re-posted 17 days ago


Job description

Job details
Job Role
Data Science Consultant 1
Career Role
Analyst - Data Science
Work Location
Charlotte, NC, Dallas, TX, Houston, TX, Raleigh, NC, Richardson, TX
State / Region / Province
North Carolina, Texas
Country
USA
Domain
Delivery
Interest Group
Infosys Limited
Company
ITL USA
Requisition ID
151775BR
Technical Skills 1
Technology|Machine Learning|Generative AI
Technical Skills 2
Technology|Agentic AI|Agent Engineering
Technical Skills 3
Technology|Generative AI|Prompt Engineering
Technical Skills 4
Technology|Generative AI|Conversational AI Platform
Technical Skills 5
Technology|AI Hyperscalers|Azure Agentic AI Services
Overview
Infosys Topaz is an AI-first suite of services, solutions, and platforms designed to accelerate business value through generative AI technologies. It amplifies the potential of individuals, enterprises, and communities by fostering unprecedented innovations, pervasive efficiencies, and connected ecosystems. Leveraging Infosys' applied AI framework, Topaz empowers users to deliver cognitive solutions that drive growth, build interconnected ecosystems, and unlock efficiencies at scale. Join us to be part of a pioneering team at the forefront of AI innovation. At Infosys Topaz, you'll have the opportunity to work with cutting-edge technologies, collaborate with industry experts, and contribute to transformative projects that shape the future of business. We are committed to fostering a culture of continuous learning and growth, ensuring that our team members thrive in a dynamic and supportive environment. If you're passionate about AI and eager to make a significant impact, Infosys Topaz is the perfect place for you to grow and excel.
In the assigned Job Role of Data Science Consultant 1, your Area Of Responsibility will be as below:
• Participate in data extraction, transformation, and preparation.
• Resolve common data issues and ensure quality for model development.
• Participate in developing models using statistical or machine learning techniques and collaborate with technology teams to operationalize them into analytics tools or scripts.
• Participate in model testing and validation, selecting the best-performing algorithms based on statistical and business metrics.
• Participate in the development of advanced analytics and machine learning or deep learning models including LLMs using predefined processes and tools like SAS and R/ Python.
• Participate in defining analytics problems; execute visualization, analysis, and predictive modeling with senior support.
• Identify data sources and extract from RDBMS and develop UI/UX for client usage.
• Participate in model performance, while making minor adjustments, and escalate risks or compliance concerns and generate reports on deviations or schedule slippages.
• Proactively participate in detailed documentation of model development, testing, and deployment activities for reproducibility.
• Work closely with business and technology teams to translate requirements into actionable models, while communicating results effectively.
• Apply predefined quality measurement frameworks, if any, to individual project tasks.
• Participate in deploying analytics tools in test and production environment, while ensuring they meet operational requirements.
Your contribution to the team:
• Strong analytical and problem-solving mindset with hands-on model development skills.
• Ability to translate business needs into actionable analytics solutions.
• Focus on data quality, validation and performance optimization.
• Effective collaboration with business and technology stakeholders.
• Commitment to continuous learning, knowledge sharing, fostering team development.
Required Skill and Experience
• Enterprise GenAI and Agentic AI solutions across RAG, AI agents, conversational AI, enterprise search, workflow automation, document intelligence, and AI copilots; comfortable with planner-executor, reflection, multi-agent, and graph-based orchestration patterns.
• Hands-on with orchestration frameworks (LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, CrewAI) and vector databases (Pinecone, Weaviate, Milvus, pgvector, FAISS, ChromaDB, Azure AI Search); working knowledge of grounding, prompt engineering, and context management.
• Experience integrating GenAI with Azure OpenAI, AWS Bedrock, Vertex AI, OpenAI, Anthropic, and Gemini, along with enterprise APIs, middleware, and data platforms.
• Knowledge of AI governance, LLMOps, evaluation, observability, guardrails, model safety, compliance, and cloud-native deployment.
Preferred Skill and Experience
• Exposure to open-source LLM ecosystems - Hugging Face, PyTorch, LoRA, QLoRA, PEFT - and models such as Llama, Mistral, Gemma, DeepSeek, and Falcon.
• Familiarity with multimodal AI, including vision-language models, speech and audio models, and image or video generation.
• Familiarity with DevOps and IaC tooling (GitHub Actions, Jenkins, Terraform, Helm, Kubernetes) and awareness of front-end stacks (React, Angular, TypeScript, GraphQL) used in copilot interfaces.
Additional Required Qualifications
• Bachelor's degree or foreign equivalent required from an accredited institution. Will also consider three years of progressive experience in the specialty in lieu of every year of education.
• This position may require relocation and/or travel to work/project location.
• All applicants authorized to work in the United States are encouraged to apply.
Benefits
Along with competitive pay, as a full-time Infosys employee you are also eligible for the following benefits:
  • Medical/Dental/Vision/Life Insurance
  • Long-term/Short-term Disability
  • Health and Dependent Care Reimbursement Accounts
  • Insurance (Accident, Critical Illness , Hospital Indemnity, Legal)
  • 401(k) plan and contributions dependent on salary level
  • Paid holidays plus Paid Time Off
About Us
Infosys is a global leader in next-generation digital services and consulting. We enable clients in more than 50 countries to navigate their digital transformation. With over four decades of experience in managing the systems and workings of global enterprises, we expertly steer our clients through their digital journey. We do it by enabling the enterprise with an AI-powered core that helps prioritize the execution of change. We also empower the business with agile digital at scale to deliver unprecedented levels of performance and customer delight. Our always-on learning agenda drives their continuous improvement through building and transferring digital skills, expertise, and ideas from our innovation ecosystem.
EEO
Infosys provides equal employment opportunities to applicants and employees without regard to race; color; sex; gender identity; sexual orientation; religious practices and observances; national origin; pregnancy, childbirth, or related medical conditions; status as a protected veteran or spouse/family member of a protected veteran; or disability.