Role Type : Full-time

Role Overview :

EDMO 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 EDMO's platform.

Key Responsibilities :

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 EDMO's AI strategy.

- Contribute to hiring, career development, and setting the technical bar for AI roles at EDMO.

Required Experience :

- 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 :

1. Large language models and orchestration (prompting, tools, agents, RAG).

2. Document understanding (OCR, layout, extraction, classification, semantic search).

3. 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).