Job Summary

The Customer Success Manager will own the end-to-end customer journey for BharatGen's AI engagements - from pre-onboarding alignment through deployment, adoption, and renewal — across projects involving large language models (text), speech technologies (ASR/TTS), and document understanding (OCR, extraction, classification). The CSM acts as the primary bridge between customers and BharatGen's engineering, research, and product teams, ensuring measurable outcomes and long-term partnership value.

Key Responsibilities

1. Customer Engagement & Relationship Management

Serve as the single point of contact for assigned customer accounts throughout the engagement lifecycle.
Build and maintain trusted relationships with customer stakeholders, including business sponsors, IT teams, and end users.
Conduct regular cadence calls, business reviews (BRs), and executive check-ins.
Understand customer business objectives and map them to BharatGen's AI capabilities in text, speech, and document understanding.
Identify expansion opportunities (upsell/cross-sell) and collaborate with sales on account growth.
Manage escalations end-to-end, coordinating internal teams for timely resolution.

2. Presales & New Inbound Leads Engagement

Partner with sales/Lead the pre-sales cycle as the solution and delivery voice for text, speech, and document understanding opportunities.
Conduct discovery workshops with prospects to capture business problems, data landscape, language/dialect requirements, volumes, and integration constraints.
Design solution approaches and scope PoCs/pilots: define objectives, datasets, evaluation metrics, timelines, and success/exit criteria.
Lead or coordinate PoC execution with engineering/research teams and present outcomes to prospect stakeholders.
Own proposal writing end-to-end: draft technical and commercial proposals, RFP/RFI/EOI responses, solution notes, and bid documents in collaboration with sales, engineering, and legal.
Prepare effort estimates, delivery plans, staffing assumptions, and pricing inputs for proposals.
Develop presales collateral: capability decks, solution one-pagers, demo scripts, and reference architectures for text/speech/document AI use cases.
Deliver product demonstrations and technical presentations to prospect business and IT teams.
Maintain a reusable proposal library (boilerplates, case studies, compliance responses) to improve bid turnaround time and win rates.
Ensure smooth presales-to-delivery handover: transfer commitments, assumptions, and scope into onboarding and delivery plans.

3. Customer Onboarding

Design and execute structured onboarding plans covering kickoff, requirement discovery, success criteria definition, and stakeholder alignment.
Facilitate technical onboarding: API access, model access, environment setup, data ingestion pipelines, and security/compliance requirements.
Coordinate data readiness activities — corpus collection, annotation guidelines, speech data quality checks, document sample validation — with customer and internal teams.
Define and document measurable success metrics (e.g., WER targets for speech, extraction accuracy for documents, task-level quality benchmarks for text/LLM use cases).
Deliver training and enablement sessions for customer teams on product usage, prompt design, integration patterns, and best practices.
Establish governance structure: communication channels, escalation matrix, meeting cadence, and RACI.

4. Project Delivery & Execution

Own delivery plans for AI engagements: milestones, timelines, dependencies, and risk registers.
Coordinate cross-functional execution across ML engineers, research teams, data/annotation teams, and DevOps for:
Text/LLM projects: fine-tuning, RAG implementations, evaluation, guardrails, and deployment.
Speech projects: ASR/TTS model customization, language/dialect coverage, telephony or streaming integrations.
Document understanding projects: OCR pipelines, layout analysis, entity extraction, classification, and human-in-the-loop workflows.
Track project health (scope, schedule, quality, budget) and publish weekly/fortnightly status reports to customers and internal leadership.
Manage UAT cycles, feedback loops, model iteration plans, and sign-off processes.
Ensure smooth go-live and hypercare support, followed by transition to steady-state support.
Maintain delivery documentation: SOWs, change requests, acceptance criteria, and closure reports.

5. Adoption, Value Realization & Retention

Monitor usage metrics, model performance, and business KPIs post-deployment; drive corrective actions where adoption lags.
Quantify and communicate ROI/value delivered (e.g., turnaround time reduction, automation rates, accuracy improvements).
Build customer health scorecards and proactively mitigate churn risks.
Drive renewals in partnership with sales and commercial teams.
Capture case studies, testimonials, and references from successful engagements.

6. Voice of Customer & Internal Collaboration

Channel structured customer feedback into product and research roadmaps.
Report recurring issues, feature gaps, and language/domain coverage requests to product teams.
Contribute to playbooks, onboarding templates, and success frameworks for repeatable delivery.

Required Skills & Qualifications

4–8 years in customer success, delivery management, or technical account management, preferably in AI/ML, SaaS, or enterprise software.
Working knowledge of NLP/LLMs, speech technologies (ASR/TTS), and document AI (OCR, IDP) — able to discuss accuracy metrics, data requirements, and integration approaches credibly.
Experience managing enterprise or government engagements; familiarity with Indian language technology ecosystems is a strong plus.
Strong project management skills (Agile/hybrid); PMP/CSM certification desirable.
Excellent communication, stakeholder management, and executive presentation skills.
Comfort with tools: JIRA/Asana, CRM (HubSpot/Salesforce), dashboards (Grafana/Looker/Excel).
Proven presales experience: proposal/RFP writing, solution scoping, PoC design, and technical demos; strong business writing skills.