14 days ago
Bengaluru, IndiaStaff+
Responsibilities
- Design and deploy scalable, secure, resilient cloud-native AI infrastructure on AWS, Azure, or GCP.
- Define architecture patterns for RAG, semantic search, multi-agent orchestration, and fine-tuning frameworks.
- Architect autonomous and multi-agent systems with planning, tool-calling, memory, inter-agent communication, and interoperability protocols.
- Establish guardrails, human-in-the-loop checkpoints, evaluation frameworks, observability, alerting, and rollback strategies for agentic workflows.
- Architect LLMOps/MLOps pipelines for data ingestion, evaluation, versioning, and deployment.
- Implement AI infrastructure cost-management strategies, including caching, rightsizing, reserved instances, and agent-call budget controls.
- Apply security, governance, responsible AI, RBAC, network segmentation, IAM, audit trails, and tool-access controls.
- Advise senior executives and business leaders on AI capabilities and business value.
- Mentor data scientists, MLOps engineers, and software developers while contributing reusable code, reference architectures, and IaC templates.
Requirements
- Deep demonstrable expertise in at least one hyperscaler: AWS, Azure, or GCP.
- Cloud AI/ML certifications such as AWS Solutions Architect, AWS AI Practitioner, GCP Professional Cloud Architect, or Azure AI Engineer are strongly preferred.
- Proven experience architecting and shipping enterprise-scale generative AI and LLM solutions, including RAG pipelines, semantic search, fine-tuning, and prompt/context engineering.
- Hands-on experience building or architecting multi-agent systems with frameworks such as LangGraph, AutoGen, CrewAI, Bedrock Agents, Azure AI Agent Service, or Vertex AI Agent Builder.
- Working knowledge of Model Context Protocol and Agent-to-Agent communication standards.
- Strong MLOps/LLMOps experience with ML CI/CD, model versioning, evaluation frameworks, and observability platforms.
- Knowledge of AI governance, security, responsible AI, IAM, VPC/network segmentation, data classification, RBAC, and auditability.
- Track record of translating business problems into scalable, production-ready AI architecture, including AI FinOps and infrastructure rightsizing.
- Bachelor's, master's, or PhD in Computer Science, Engineering, or a related field.
- Proficient English language skills at C2 level.
Benefits
- Hybrid work arrangement in a regular, day-shift role based in India.
- Hands-on experience, mentorship, and world-class learning opportunities.
- Opportunity to lead AI-powered transformation and solve enterprise business challenges.
- Values-driven, inclusive work environment with integrity, curiosity, and innovation.
Tech Stack
Categories
About Genpact
Genpact is a global professional services and technology firm that runs and transforms mission-critical operations for large enterprises through consulting, managed services, and AI- and analytics-driven platforms. It serves industries such as banking, insurance, healthcare, and manufacturing/supply chain, modernizing finance, risk, customer service, and back-office processes. Headquartered in New York and listed on the NYSE (G), Genpact originated within GE before becoming an independent public company.