Lead consultant - GenAI LLM Ops Engineer

Genpact (NYSE G) is a global professional services and solutions firm delivering outcomes that shape the future. Our 125,000+ people across 30+ countries are driven by our innate curiosity, entrepreneurial agility, and desire to create lasting value for clients. Powered by our purpose - the relentless pursuit of a world that works better for people - we serve and transform leading enterprises, including the Fortune Global 500, with our deep business and industry knowledge, digital operations services, and expertise in data, technology, and AI.
Inviting applications for the role of Lead consultant - GenAI LLM Ops Engineer, we're looking for an LLM Ops Engineer to build, operate, and scale our Large Language Model platforms and applications. You'll own the end-to-end operational lifecycle-from model deployment and orchestration to reliability, observability, safety, cost optimization, and performance tuning. You'll partner closely with Data Science, MLOps, Security, and Product teams to deliver robust, compliant, and efficient LLM-powered experiences.
Responsibilities
.Architect secure, reusable, and modular infrastructure-as-code (IaC) frameworks for GenAI and LLM operations
.Design, deploy, and maintain LLM serving infrastructure (e.g., Azure OpenAI, self-hosted OSS models, vector databases).
.Implement model orchestration (routing, ensemble strategies, fallbacks, retries, cache layers).
.Build CI/CD pipelines for prompt catalogs, model configurations, guardrails, and evaluation suites.
.Define and track LLM-specific SLOs (latency, response quality, safety violations, hallucination rate).
.Implement telemetry (traces, logs, metrics, prompt/response analytics) and A/B experiments.
.Establish alerting & incident response playbooks.
.Lead the development and standardization of CI/CD pipelines for AI/ML model deployment
.Ensure security, privacy, and regulatory compliance (data residency, consent, auditability).
.Manage prompt governance (versioning, approval workflow, change logs, rollback).
.Define and enforce best practices for model versioning, governance and lifecycle management
.Troubleshoot and resolve issues related to LLM deployment, scaling, and performance
.Stay updated with advancements in MLOps, LLMs, and GenAI technologies

Qualifications we seek in you!
Minimum Qualifications
.Bachelor's degree in Computer Science, Engineering, or a related field
.Proven experience in MLOps, DevOps, or AI/ML infrastructure roles
.Hands-on experience with CI/CD pipelines, containerization, and orchestration tools (e.g., Docker, Kubernetes)
.Proficiency in scripting and programming languages such as Python, Bash, or similar
.Experience with cloud platforms (AWS, Azure, GCP) and infrastructure-as-code tools (Terraform, CloudFormation)
.Strong understanding of machine learning model lifecycle management and operationalization
.Knowledge of data privacy, security, and compliance standards in AI/ML environments

Preferred Qualifications
. Master's degree in a relevant field
. Experience with large language models (LLMs) and generative AI frameworks
. Familiarity with monitoring, logging, and observability tools for AI/ML workloads
. Experience collaborating with cross-functional teams in enterprise environments
. Excellent problem-solving, communication, and documentation skills
. Prior experience mentoring or leading technical teams
Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values diversity and inclusion, respect and integrity, customer focus, and innovation. Get to know us at genpact.com and on LinkedIn, X, YouTube, and Facebook. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.