We are looking for an AI Consultant to help the largest global enterprises get real business value from Artificial Intelligence on AWS, as part of AWS Pro Serve India LLP ("Pro Serve India"). In this role, you will design and build Machine Learning (ML), Deep Learning (DL), generative AI and agentic AI solutions that run on large volumes of enterprise data and solve a wide range of business problems.
The ideal candidate has hands-on experience building ML and DL models and agentic AI systems, including multi-agent orchestration, tool use and agent frameworks such as Amazon Bedrock Agent Core. You enjoy diving deep into data, analysing it, finding root causes and designing long-term solutions. You are customer obsessed, love to learn, and want to innovate.
You will work closely with AWS customers, partners and internal teams, learning from many enterprise use cases and building on Amazon's decades of AI innovation
Key job responsibilities
-Understand the internal customer’s business need and guide them to a solution using our AWS AI Services, AWS AI Platforms, AWS AI Frameworks, and AWS AI EC2 Instances .
-Assist internal customers by being able to deliver a ML / DL project from beginning to end, including understanding the business need, aggregating data, exploring data, building & validating predictive models, and deploying completed models to deliver business impact to the organization.
-Use Deep Learning frameworks like MXNet, Caffe 2, Tensorflow, Theano, CNTK, and Keras to help our internal customers build DL models. *Use SparkML and Amazon Machine Learning (AML) to help our internal customers build ML models.
-Work with our Qualified Services Big Data consultants to analyze, extract, normalize, and label relevant data.



*Work with our Professional Services Dev Ops consultants to help our internal customers operationalize models after they are built.
-Assist internal customers with identifying model drift and retraining models.
-Research and implement novel ML and DL approaches, including using FPGA.
-Expertise in delivery Agentic and Generative AI solutions
About the team
About AWS:
Diverse Experiences: AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job below, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture - Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and Amaze Con conferences,



inspire us to never stop embracing our uniqueness.
Mentorship & Career Growth - We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

BASIC QUALIFICATIONS

- 8+ years of building machine learning models or developing algorithms for business application experience
- Hands-on experience building agentic AI systems, including multi-agent orchestration, tool and API integration, memory and guardrails, using frameworks such as Amazon Bedrock Agent Core, Strands Agents, Lang Graph or CrewAI .
- Experience with AWS AI/ML services such as Amazon Bedrock, Amazon Sage Maker and Amazon Connect, plus related data and analytics services .
- Experience with prompt engineering, Retrieval-Augmented Generation (RAG), model fine-tuning and evaluating LLM-based applications .
- Proficiency in Python and MLOps/LLMOps practices, including CI/CD, infrastructure as code and observability.

PREFERRED QUALIFICATIONS

- Experience in customer-facing consulting roles, including turning business problems into technical solutions and presenting to technical and business stakeholders.
- Experience working with and enabling partner delivery teams.
- AWS certifications such as AWS Certified Machine Learning – Specialty, AWS Certified AI Practitioner or AWS Certified Solutions Architect .
- Master's degree or PhD in Computer Science, Machine Learning, Statistics or a related field.
Our inclusive culture empowers Amazonians to deliver the best results for our customers.

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