Lead consultant-AWS AI

Ready to shape the future of work?

At Genpact, we don’t just adapt to change—we drive it. AI and digital innovation are redefining industries, and we’re leading the charge. Genpact’s AI Gigafactory, our industry-first accelerator, is an example of how we’re scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to agentic AI, our breakthrough solutions tackle companies’ most complex challenges.

If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that’s shaping the future, this is your moment.

Genpact (NYSE : G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions – we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation, our teams implementdata, technology, and AI to create tomorrow, today. Get to know us at genpact.com and on LinkedIn, X, YouTube, and Facebook.

Inviting applications for the role of Lead Consultant-AWS AI / ML Engineer

Responsibilities

Design, develop, and deploy scalable AI / ML solutions using AWS services such as Amazon Bedrock, SageMaker, Amazon Q, Amazon Lex, Amazon Connect, and Lambda.

Implement and optimize large language model (LLM) applications using Amazon Bedrock, including prompt engineering, fine-tuning, and orchestration for specific business use cases.

Build and maintain end-to-end machine learning pipelines using SageMaker for model training, tuning, deployment, and monitoring.

Integrate conversational AI and virtual assistants using Amazon Lex and Amazon Connect, with seamless user experiences and real-time inference.

Leverage AWS Lambda for event-driven execution of model inference, data preprocessing, and microservices.

Design and maintain scalable and secure data pipelines and AI workflows, ensuring efficient data flow to and from Redshift and other AWS data stores.

Implement data ingestion, transformation, and model inference for structured and unstructured data using Python and AWS SDKs.

Collaborate with data engineers and scientists to support development and deployment of ML models on AWS.

Monitor AI / ML applications in production, ensuring optimal performance, low latency, and cost efficiency across all AI / ML services.

Ensure implementation of AWS security best practices, including IAM policies, data encryption, and compliance with industry standards.

Drive the integration of Amazon Q for enterprise AI-based assistance and automation across internal processes and systems.

Participate in architecture reviews and recommend best-fit AWS AI / ML services for evolving business needs.

Stay up to date with the latest advancements in AWS AI services, LLMs, and industry trends to inform technology strategy and innovation.

Prepare documentation for ML pipelines, model performance reports, and system architecture.

Qualifications we seek in you :

Minimum Qualifications

Proven hands-on experience with Amazon Bedrock, SageMaker, Lex, Connect, Lambda, and Redshift.

Strong knowledge and application experience with Large Language Models (LLMs) and prompt engineering techniques.

Experience building production-grade AI applications using AWS AI or other generative AI services.

Solid programming experience in Python for ML development, data processing, and automation.

Proficiency in designing and deploying conversational AI / chatbot solutions using Lex and Connect.

Experience with Redshift for data warehousing and analytics integration with ML solutions.

Good understanding of AWS architecture, scalability, availability, and security best practices.

Familiarity with AWS development, deployment, and monitoring tools (CloudWatch, CodePipeline, etc.).

Strong understanding of MLOps practices including model versioning, CI / CD pipelines, and model monitoring.

Strong communication and interpersonal skills to collaborate with cross-functional teams and stakeholders.

Ability to troubleshoot performance bottlenecks and optimize cloud resources for cost-effectiveness

Preferred Qualifications :

AWS Certification in Machine Learning, Solutions Architect, or AI Services.

Experience with other AI tools (e.g., Anthropic Claude, OpenAI APIs, or Hugging Face).

Knowledge of streaming architectures and services like Kafka or Kinesis.

Familiarity with Databricks and its integration with AWS services.

Why join Genpact?

Be a transformation leader – Work at the cutting edge of AI, automation, and digital innovation

Make an impact – Drive change for global enterprises and solve business challenges that matter

Accelerate your career – Get hands-on experience, mentorship, and continuous learning opportunities

Work with the best – Join 140,000+ bold thinkers and problem-solvers who push boundaries every day

Thrive in a values-driven culture – Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress

Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters : Up.

Let’s build tomorrow together.