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EXL
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Senior Manager

Senior Manager

EXL

10 years

0 Lacs

hyderabad telangana india

Posted:8 hours ago| Platform:

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Skills Required

ai management strategy planning ml portfolio compliance mentoring data discovery engineering model evaluation latency reliability drift metrics monitoring security drive design marketing coaching support positioning packaging pricing sql healthcare orchestration aws gcp azure databricks testing content retention governance

Work Mode

On-site

Job Type

Full Time

Job Description

Position Summary The Senior Manager, AI Product Management will lead the end-to-end strategy, planning, and delivery of AI/ML products and capabilities. This role is accountable for portfolio outcomes, cross-functional alignment, and adherence to responsible AI and compliance standards while mentoring a team of product managers.

Primary Responsibilities

Define the AI product strategy and roadmap aligned to business objectives and user needs.
Prioritize initiatives based on ROI, feasibility, data readiness, and risk.
Lead discovery, proof-of-concept and pilot initiatives, and general availability launches with clear stage gates.
Partner with Data Science and Engineering on model lifecycle, evaluation, performance (latency/cost), and reliability (SLA/SLO).
Establish robust observability: data and model drift, quality metrics, safety and hallucination monitoring, and feedback loops.
Ensure compliance with privacy, security, and regulatory requirements (e.g., PII, GDPR/CCPA, SOC 2, and domain-specific standards).
Drive cross-functional alignment with Design, Legal/Privacy/Security, Marketing, Sales, Customer Success, and Operations.
Manage and develop product managers; set objectives, provide coaching, and support career progression.
Lead go-to-market efforts including positioning, packaging, pricing, and field enablement.

Minimum Qualifications

7–10+ years of product management experience, including 4+ years in AI/ML or data products and 2+ years managing product managers.
Demonstrated success delivering AI/ML or GenAI products at scale.
Proficiency in AI/ML concepts (LLMs, RAG, agents, evaluation) and MLOps practices.
Quantitative aptitude, including experiment design, metrics, and basic SQL; strong written and verbal communication.
Experience with privacy, security, and responsible AI practices.

Preferred Qualifications

Industry expertise in [e.g., financial services, healthcare, commerce, enterprise SaaS].
Familiarity with modern AI infrastructure (vector databases, orchestration frameworks, GPUs) and cost/latency optimization.
Experience with major cloud providers (AWS/GCP/Azure), data platforms (Snowflake/Databricks), and observability tools.
Exposure to safety testing, red teaming, and content moderation.
Advanced degree (MBA or technical field) preferred.

Key Performance Indicators

Business outcomes: revenue impact, conversion/retention, cost-to-serve, time-to-resolution.
Product performance: adoption, activation, satisfaction (CSAT/NPS).
AI quality: accuracy, hallucination rate, drift metrics, latency (p95), and cost per request.

Initial 30-60-90 Day Objectives

30 Days: Assess portfolio, data readiness, metrics, and risks; conduct stakeholder and customer discovery; identify priority opportunities.
60 Days: Deliver a staged roadmap; establish evaluation and monitoring frameworks; align go-to-market plans.
90 Days: Launch initial pilot/GA; operationalize monitoring and feedback mechanisms; publish governance artifacts

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