Position: Senior AI Lead – Document, Conversational \& Data Intellige
Location: Pune
Working Days: 5 (mon\-fri)
Experience Required: 6\-10 Years
- *Role Overview**
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Our Client is hiring a Senior AI Lead to own and scale our AI stack across document intelligence, conversational intelligence, and data intelligence. You will turn prototypes into robust, production\-grade capabilities that integrate deeply with customer systems and meet strict standards for scale, reliability, and security.
You will work closely with product and engineering leadership, lead a small high\-performing AI team, and directly influence how universities and institutions experience Our Client’s platform.
- *Key Responsibilities**
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### **1\. AI Strategy \& Architecture**
- Define and own the end\-to\-end AI architecture across document, conversational, and data intelligence.
- Design multi\-tenant, cloud\-native AI services optimized for performance, cost, and reliability.
- Establish standards for prompt engineering, tool/agent orchestration, RAG, fine\-tuning, evaluation, and monitoring.
- Translate product requirements into clear technical designs, milestones, and delivery plans.
### **2\. Document Intelligence**
- Lead design and implementation of document understanding pipelines for transcripts, forms, financial docs, policies, and knowledge bases.
- Build capabilities for OCR, layout analysis, entity extraction, classification, validation, and summarization.
- Implement retrieval\-augmented generation over large document corpora, including indexing, chunking, and relevance tuning.
- Define quality metrics and automated evaluation suites to continuously improve accuracy, robustness, and latency.
### **3\. Conversational Intelligence**
- Own the architecture of production\-grade chat and voice assistants across web, mobile, and telephony channels.
- Design agentic workflows combining LLMs, tools/APIs, memory, and business rules to support complex student and staff journeys.
- Implement guardrails, policies, and UX patterns to minimize hallucinations and ensure safe, compliant responses.
- Set up a rigorous evaluation framework for conversation quality, containment, user satisfaction, and escalation performance.
### **4\. Customer System Integrations**
- Architect and oversee integrations with customer CRMs, SIS, telephony, and data platforms (e.g., Salesforce, contact centers, data warehouses).
- Define API and event\-driven integration patterns for both real\-time and batch scenarios.
- Ensure AI features respect tenant boundaries, roles/permissions, and customer\-specific configurations.
- Partner with solutions/implementation teams to make deployment repeatable, configurable, and maintainable across institutions.
### **5\. Data Intelligence \& Analytics**
- Collaborate with data engineering to design data models and pipelines that power AI features and insights.
- Lead development of models and heuristics for scoring, routing, prioritization, and personalization based on behavioral and conversational signals.
- Define and maintain dashboards and KPIs for AI performance, adoption, and business impact.
- Drive an experimentation culture with A/B tests, staged rollouts, and data\-driven iteration.
### **6\. Production, Scale \& Security**
- Ensure all AI services meet enterprise standards for uptime, resiliency, and observability.
- Define and enforce best practices for logging, tracing, alerting, and model/service health monitoring.
- Work with security and compliance teams to align with data privacy regulations, including encryption, access control, and data retention policies relevant to education.
- Implement robust processes for model and configuration versioning, canary deployments, and safe rollbacks.
### **7\. Leadership \& Collaboration**
- Lead and mentor AI/ML engineers, data scientists, and AI application engineers.
- Collaborate closely with product, platform engineering, implementation, and customer success to ensure AI capabilities deliver real outcomes.
- Participate in key customer meetings to understand requirements, shape solutions, and represent Our Client’s AI strategy.
- Contribute to hiring, career development, and setting the technical bar for AI roles at Our Client.
- *Required Experience**
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- 6–10 years of experience in software engineering and/or applied ML, with at least 4–5 years focused on building AI products.
- Proven track record of taking AI solutions (LLM or traditional ML) from PoC to production in a SaaS or enterprise environment.
- Hands\-on experience with:
+ Large language models and orchestration (prompting, tools, agents, RAG).
+ Document understanding (OCR, layout, extraction, classification, semantic search).
+ Conversational AI (chatbots, voicebots, agent assist) with measurable outcomes.
- Strong programming skills in one or more of: Python, Node.js, Java/Scala (or similar).
- Experience designing and operating cloud\-native services (containers, CI/CD, infrastructure as code).
- Experience integrating with enterprise systems such as CRMs, telephony platforms, and data platforms.
- Familiarity with security and compliance considerations in regulated industries (education, healthcare, finance, or similar).