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Generative Ai Analyst Jobs (NOW HIRING)

Strike is seeking a motivated and detail-oriented AI Analyst to support the development and ... Familiarity with generative AI tools or APIs. ** Must have USA work authorization. Sponsorship not ...

Strike is seeking a motivated and detail-oriented AI Analyst to support the development and ... Familiarity with generative AI tools or APIs. ** Must have USA work authorization. Sponsorship not ...

AI/ML Engineer - Generative AI Location: New York, NY 10004 (Onsite. LOCAL CANDIDATES ONLY ... Demonstrate strong experience in enterprise?level data ingestion, transformation, analysis, and ...

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How much do generative ai analyst jobs pay per year?

As of Jun 10, 2026, the average yearly pay for generative ai analyst in the United States is $88,569.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,000.00 and $99,500.00 per year, depending on experience, location, and employer.

What is the difference between Generative Ai Analyst vs Data Scientist?

AspectGenerative Ai AnalystData Scientist
Required CredentialsBachelor's in CS, AI, or related fields; certifications in AI/MLBachelor's/Master's in CS, Statistics, or related fields; advanced certifications
Work EnvironmentTech companies, AI startups, research labsTech firms, finance, healthcare, consulting
Employer & Industry UsageFocus on developing and refining generative AI modelsAnalyze data, build predictive models, derive insights
Common Search & Comparison IntentUnderstanding roles in AI developmentData analysis and modeling skills

While both roles require strong technical skills and knowledge of AI and data analysis, a Generative Ai Analyst specializes in creating and optimizing generative AI models, whereas a Data Scientist focuses on analyzing data to inform business decisions. The roles often overlap but differ in their primary focus and application within organizations.

What are the key skills and qualifications needed to thrive as a Generative AI Analyst, and why are they important?

To thrive as a Generative AI Analyst, you need a solid background in data science, machine learning, and statistics, often supported by a degree in computer science or a related field. Familiarity with tools and frameworks such as Python, TensorFlow, PyTorch, and experience with large language models or generative adversarial networks (GANs) is typically required. Strong analytical thinking, creativity, and effective communication skills help you interpret complex data and present insights to stakeholders. These skills and qualities are crucial for developing innovative AI solutions, solving business challenges, and driving impactful results.

How does a Generative AI Analyst typically collaborate with data scientists and engineering teams?

A Generative AI Analyst frequently works alongside data scientists and engineering teams to interpret model outputs, assess data quality, and help translate business objectives into technical requirements. Collaboration usually involves regular meetings to review model performance, troubleshoot issues, and refine algorithms based on real-world feedback. Effective communication and a shared understanding of both AI concepts and business goals are essential, as the analyst often serves as a bridge between technical teams and stakeholders. This collaborative environment fosters continuous learning and innovation, making teamwork a core aspect of the role.

What is a Generative AI Analyst?

A Generative AI Analyst is a professional who specializes in analyzing, designing, and optimizing systems that use generative artificial intelligence models, such as large language models or image generators. Their work involves understanding how these AI models are developed, deployed, and utilized across various applications. They assess data quality, monitor model outputs, evaluate performance, and help improve the effectiveness and ethical use of generative AI technologies. Generative AI Analysts may also provide insights to organizations on best practices, risk management, and innovation opportunities related to AI. Their expertise bridges the gap between data science, AI development, and business strategy.
More about Generative Ai Analyst jobs
What cities are hiring for Generative Ai Analyst jobs? Cities with the most Generative Ai Analyst job openings:
What states have the most Generative Ai Analyst jobs? States with the most job openings for Generative Ai Analyst jobs include:
What job categories do people searching Generative Ai Analyst jobs look for? The top searched job categories for Generative Ai Analyst jobs are:
Infographic showing various Generative Ai Analyst job openings in the United States as of June 2026, with employment types broken down into 84% Full Time, 6% Part Time, and 10% Contract. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution, with an average salary of $88,569 per year, or $42.6 per hour.
Generative AI Platform Architect - Evinova

Generative AI Platform Architect - Evinova

AstraZeneca

Gaithersburg, MD

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 21 days ago


AstraZeneca rating

8.6

Company rating: 8.6 out of 10

Based on 43 frontline employees who took The Breakroom Quiz

16th of 71 rated pharmaceutical


Job description

Job Title: Generative AI Platform Architect - Evinova
Location: Gaithersburg, MD

At AstraZeneca, we pride ourselves on crafting a collaborative culture that champions knowledge-sharing, ambitious thinking and innovation - ultimately providing employees with the opportunity to work across teams, functions and even the globe.

Recognizing the importance of individualized flexibility, our ways of working allow employees to balance personal and work commitments while ensuring we continue to create a strong culture of collaboration and teamwork by engaging face-to-face in our offices 3 days a week. Our head office is purposely designed with collaboration in mind, providing space where teams can come together to strategize, brainstorm and connect on key projects.Comprehensive relocation packages available for qualified candidates.

Are you ready to be part of the future of healthcare? Can you think big, be bold, and harness the power of digital and AI to tackle longstanding life sciences challenges? Then Evinova, a global health tech business might be for you!

Transform patients' lives through technology, data, and innovative ways of working. You're disruptive, decisive, and transformative. Someone excited to use technology to improve patients' health. We're building a new Health-tech business - Evinova, a fully-owned subsidiary of AstraZeneca Group.

Evinova delivers market-leading digital health solutions that are science-based, evidence-led, and human experience-driven. Thoughtful risks and quick decisions come together to accelerate innovation across the life sciences sector. Be part of a diverse team that pushes the boundaries of science by digitally empowering a deeper understanding of the patients we're helping. Launch pioneering digital solutions that improve the patients' experience and deliver better health outcomes. Together, we have the opportunity to combine deep scientific expertise with digital and artificial intelligence to serve the wider healthcare community and create new standards across the sector.

Introduction to Role:

The Machine Learning and Artificial Intelligence Operations team (ML/AI Ops) is a newly formed team will spearhead the design, creation, and operational excellence of our entire Generative AI, agentic systems, and LLM computational AWS ecosystem to catalyze and accelerate science led innovations.

This team is responsible and accountable for the design, implementation, deployment, health and performance of all algorithms, models, Generative AI operations (GenAI Ops, AIOps, and LLMOps) and Data Science Platform. We manage Generative AI and broader cloud resources, automating operations through infrastructure-as-code and CI/CD pipelines, and ensure best-in-class operations - striving to push even beyond mere compliance with industry standards such as Good Clinical Practices and Good Machine Learning Practice (GMLP).

As the Generative AI Platform Architect on our team, you will architect and oversee the global cloud ML/AI infrastructure that underpins our entire ML/AI value proposition. You will design, implement, and manage scalable cloud solutions using AWS services while establishing ML/AI governance frameworks, automating infrastructure with tools like AWS CDK and Projen, and conducting cost-benefit analyses of foundation models to drive strategic decisions across the organization.

This position requires a deep understanding of cloud-native Generative AI and LLMOps methodologies, AWS infrastructure, State-of-the-art (SOTA) Foundation Models, prompt engineering pipelines, retrieval-augmented generation (RAG) architectures, and AWS GenAI Services (Bedrock, SageMaker for LLMs), and the unique demands of regulated industries, making it a cornerstone of our success in delivering impactful solutions to the pharmaceutical industry.

Accountabilities:

Operational Excellence

  • Lead by example in creating high-performance, mission-focused and interdisciplinary teams/culture founded on trust, mutual respect, growth mindsets, and an obsession for building extraordinary products with extraordinary people.
  • Drive the creation of proactive capability and process enhancements that ensures enduring value creation and analytic compounding interest.
  • Design and implement resilient cloud Generative AI and agentic system operational capabilities to maximize our system A-bilities (Learnability, Flexibility, Extendibility, Interoperability, Scalability).
  • Drive precision and systemic cost efficiency, optimized system performance, and risk mitigation with a data-driven strategy, comprehensive analytics, and predictive capabilities at the tree-and-forest level of our GenAI agent systems, workloads and processes.

Generative AI Cloud Operations and Engineering

  • Architect and implement scalable AWS agentic GenAI cloud infrastructure in a multi-tenant SaaS environment.
  • Deep understanding of challenges in deploying Generative AI applications and agents.
  • Closely follow frontier developments in Generative AI and GenAI tooling, techniques, and technologies.
  • Establish governance frameworks for agentic GenAI infrastructure management and ensure compliance with industry best practices.
  • Ensure principled and methodical validation pathways and a Well Architected Framework for Embryonic Research (WAFER) similar to and building on AWS's Well Architected Framework (WAF) for all early stage product and operational GenAI PoC's across the organization.
  • Oversee GenAI-related Kubernetes (k8s) cluster management and provide expertise on alternative GenAI workflow orchestration options such as Argo vs Kubeflow vs ECS vs AgentCore, and GenAI data pipeline creation, management and governance with tools like Airflow or others.
  • Employ tools like AWS CDK (TypeScript), Projen, and Argo CD to automate infrastructure deployment and management.
  • Help set the strategy and manage the tactical balance between framework and platform experimentation and democratization with standardization and centralized management and governance
  • Conduct cost-benefit analyses and formal processes for selection and utilization of foundation models, evaluating their architectures, performance, and costs.
  • Work with multiple teams to ensure that the platform meets organizational needs and scales effectively.

Personal Attributes:

  • Customer-obsessed and passionate about building products that solve real-world problems.
  • Highly organized and detail-oriented, with the ability to manage multiple initiatives and deadlines.
  • Collaborative and inclusive, fostering a positive team culture where creativity and innovation thrive.

Essential Skills/Experience:

  • HS Diploma and 8 years of experience in Engineering/IT solutions OR BA/BS Degree and 6 years of experience or equivalent capabilities.
  • Minimum of 10 years in cloud infrastructure design and management roles.
  • Deep understanding of the Data Science Lifecycle (DSLC) and the ability to shepherd data science projects from inception to production within the platform architecture.
  • Expert in Typescript, AWS CDK, Projen, and Argo CD and other Cloud Infrastructure CI/CD Tools
  • Strong familiarity with Python
  • Extensive experience in managing Kubernetes clusters and/or ECS for GenAI workflows.
  • Solid understanding of foundation models and their applications in GenAI solutions.
  • Strong background in AWS DevOps practices and cloud architecture.
  • Deep knowledge of AWS services (Bedrock, Sagemaker, EC2, S3, RDS, Lambda, etc) and hands-on design and implementation of cloud systems (microservices architecture, API design, and database management (SQL/NoSQL)
  • Experience with monitoring and optimizing cloud infrastructure for scalability and cost-efficiency.
  • Ability to collaborate effectively with engineering, design, product, science and security teams.
  • Strong written and verbal communication skills for reporting and documentation.
  • Demonstrated ability to manage large-scale, complex projects across an organization.
  • Proven experience in conducting performance and cost analyses of AWS infrastructure and ML/AI models.

Where can I find out more?

  • Learn more about Evinova www.evinova.com
  • Our Social Media, Follow AstraZeneca on LinkedIn https://www.linkedin.com/company/1603/
  • Follow AstraZeneca on Facebook https://www.facebook.com/astrazenecacareers/
  • Follow AstraZeneca on Instagram https://www.instagram.com/astrazeneca_careers/?hl=en
  • Our US Footprint: Powering Scientific Innovation - YouTube

Why Evinova?

Evinova is a global health tech business, separate company part of the AstraZeneca group. Together, we can accelerate the delivery of life-changing medicines, improve the design and delivery of clinical trials for better patient experiences and outcomes, and think more holistically about patient care before, during, and after treatment. We know that regulators, healthcare professionals, and care teams at clinical trial sites do not want a fragmented approach. They do not want a future where every pharmaceutical company provides its own, different digital solutions. They want solutions that work across the sector, simplify their workload, and benefit patients broadly. By bringing our solutions to the wider life sciences community, we can help build more unified approaches to how we all develop and deploy digital technologies, better serving our teams, physicians, and ultimately patients. Evinova represents a unique opportunity to deliver meaningful outcomes with digital and AI to serve the wider healthcare community and create new standards for the sector. Join us on our journey of building a new kind of health tech business to reset expectations of what a bio-pharmaceutical company can be. This means we're opening new ways to work, pioneering cutting-edge methods, and bringing unexpected teams together. Interested? Come and join our journey.

Total Rewards:

The annual base pay for this position ranges from $167,772.00 to $251,658.00.Hourly and salaried non-exempt employees will also be paid overtime pay when working qualifying overtime hours.Base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition, our positions offer a short-term incentive bonus opportunity; eligibility to participate in our equity-based long-term incentive program (salaried roles),to receive a retirement contribution (hourly roles), and commission payment eligibility (sales roles). Benefits offered included a qualified retirement program [401(k) plan]; paid vacation and holidays; paid leaves; and, health benefits including medical, prescription drug, dental, and vision coverage in accordance with the terms and conditions of the applicable plans. Additional details of participation in these benefit plans will be provided if an employee receives an offer of employment. If hired, employee will be in an "at-will position" and the Company reserves the right to modify base pay(as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.

AstraZenecais an equal opportunity employer that is committed to diversity and inclusion and providing a workplace that is free from discrimination. AstraZeneca is committed to accommodating persons with disabilities. Such accommodation is available on request in respect of all aspects of the recruitment, assessment and selection process and may be requested by emailingAZCHumanResources@astrazeneca.com.

#LI-Hybrid

Date Posted

26-Feb-2026

Closing Date

Our mission is to build an inclusive environment where equal employment opportunities are available to all applicants and employees. In furtherance of that mission, we welcome and consider applications from all qualified candidates, regardless of their protected characteristics. If you have a disability or special need that requires accommodation, please complete the corresponding section in the application form.


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