Lead Assistant Manager

Number Of Positions

4

Band

B2

Band Name

Lead Assistant Manager

Cost Code

D012603

Campus/Non Campus

NON CAMPUS

Employment Type

Permanent

Requisition Type

New

Max CTC

250000.0000 - 1050000.0000

Complexity Level

Not Applicable

Work Type

Hybrid – Working Partly From Home And Partly From Office

Group

EXL Digital

Sub Group

Digital Solutions

Organization

Digital Solutions

LOB

Product Practice Market

SBU

GenAI CoE

Country

India

City

Noida

Center

Noida - Centre 59

Skill

Minimum Qualification

Certification

No data available

• Monitor and maintain health of production AI models (GenAI and traditional ML).
• Troubleshoot data/model/infra issues across model pipelines, APIs, embeddings, and prompt systems.
• Collaborate with Engineering and Data Science teams to deploy new versions and manage rollback if needed.
• Implement automated logging, alerting, and retraining pipelines.
• Handle prompt performance drift, input/output anomalies, latency issues, and quality regressions.
• Analyze feedback and real-world performance to propose model or prompt enhancements.
• Conduct A/B testing, manage baseline versioning and monitor model outputs over time.
• Document runbooks, RCA reports, model lineage and operational dashboards.
• Support GenAI adoption by assisting in evaluations, hallucination detection, and prompt optimization.

• 1+ year of experience in Data Science, ML, or MLOps.
• Good grasp of ML lifecycle, model versioning, and basic monitoring principles.
• Strong Python skills with exposure to ML frameworks (scikit-learn, pandas, etc.).
• Basic familiarity with LLMs and interest in GenAI (OpenAI, Claude, etc.).
• Exposure to AWS/GCP/Azure or any MLOps tooling.
• Comfortable reading logs, parsing metrics, and triaging issues across the stack.
• Eagerness to work in a production support environment with proactive ownership.

• Prompt engineering knowledge (system prompts, temperature, tokens, etc.).
• Hands-on with vector stores, embedding models, or LangChain/LlamaIndex.
• Experience with tools like MLflow, Prometheus, Grafana, Datadog, or equivalent.
• Basic understanding of retrieval pipelines or RAG architectures.
• Familiarity with CI/CD and containerization (Docker, GitHub Actions).

• A strong starter who wants to go beyond notebooks and see AI in action.
• Obsessed with observability, explainability, and zero-downtime AI.
• Wants to build a foundation in GenAI while leveraging their traditional ML skills.
• A great communicator who enjoys cross-functional collaboration.

Workflow Type