AVP, GenAI Enterprise Architect

Posted Yesterday
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Hiring Remotely in United States
Remote or Hybrid
Senior level
Information Technology • Database • Consulting
The Role
Design and deploy end-to-end Generative AI systems across the 7-layer stack. Select and fine-tune models, build LLMOps pipelines, implement observability, integrate with cloud platforms and APIs, enforce data protection, and lead stakeholder workshops to translate business needs into scalable, secure AI solutions.
Summary Generated by Built In

Design and deploy enterprise-grade AI solutions (LLMs, RAG, agents) by selecting appropriate models, building data pipelines, and integrating them with cloud platforms (AWS, Azure, GCP). Lead technical strategies across the standard 7-layer GenAI stack (from data ingestion to application interfaces), ensure scalability, manage AI security/hallucinations, and bridge business needs with engineering teams.

Responsibilities
  • System Design & Architecture: Architect end-to-end Generative AI systems by operationalizing the 7-layer AI architecture (Data Sources, Preprocessing, Model Selection, Orchestration, Inference, Integration, and Application).
  • Model Selection & Tuning: Evaluate and select cutting-edge commercial (e.g., GPT-4) and open-source models, and fine-tune models for domain-specific use cases.
  • LLMOps, Observability & Pipelines: Establish LLMOps standards for model versioning and CI/CD. Implement foundational observability (OBS) layers using tools like Datadog, Splunk, or Prometheus to monitor system health, API latency, and basic application metrics.
  • Integration & Data Protection: Integrate AI solutions with existing APIs while enforcing core data protection measures, including Role-Based Access Control (RBAC), data encryption in transit, and basic PII (Personally Identifiable Information) masking to manage hallucinations and adversarial attacks.
  • Strategic Leadership: Collaborate with stakeholders to map business challenges to AI solutions and establish AI governance frameworks.
  • Client Consulting: Act as the primary onshore technical liaison, facilitating client workshops, requirements gathering, and translating business pain points into technical AI blueprints.
Qualifications
  • Consulting Skills: Exceptional client-facing communication skills; proven ability to present complex technical concepts to business stakeholders.
  • Technical Expertise: Deep knowledge of NLP, Python, deep learning frameworks (PyTorch/TensorFlow), and orchestration tools (LangChain, Autogen).
  • Cloud & Data Systems: Extensive hands-on experience with AI services on AWS, Azure, or GCP. Expertise in vector databases (e.g., Pinecone, Milvus) and embedding techniques.
  • Qualifications: Bachelor’s / Master’s in Computer Science, AI, Data Science, or related field; 8–15 years in software engineering, ML, or AI roles, with demonstrable onshore consulting experience.

Skills Required

  • 8-15 years in software engineering, ML, or AI roles with onshore consulting experience
  • Bachelor's or Master's in Computer Science, AI, Data Science, or related field
  • Deep knowledge of NLP and embedding techniques
  • Proficiency in Python
  • Experience with deep learning frameworks (PyTorch or TensorFlow)
  • Experience selecting and fine-tuning commercial and open-source LLMs (e.g., GPT-4)
  • Hands-on experience with cloud AI services on AWS, Azure, or GCP
  • Experience with vector databases (Pinecone, Milvus) and embeddings
  • Familiarity with LLMOps, model versioning, and CI/CD for ML
  • Experience implementing observability using tools like Datadog, Splunk, or Prometheus
  • Experience integrating AI with existing APIs and enforcing RBAC, encryption in transit, and PII masking
  • Experience with orchestration tools/frameworks (e.g., LangChain, Autogen)
  • Strong client-facing communication and consulting skills
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The Company
HQ: New York, NY
30,246 Employees
Year Founded: 1999

What We Do

Choosing a digital partner is about more than capabilities — it’s about collaboration and character. Unrealistic overhauls and off-the-shelf products ignore what matters most — your unique needs, culture, goals, and your legacy data and technology environments. At EXL, our collaboration is built on ongoing listening and learning to adapt our methodologies. We’re your business evolution partner—tailoring solutions that make the most of data to make better business decisions and drive more intelligence into your increasingly digital operations. Whether your goals are scaling the use of AI and digital, redesign operating models, or driving better and faster decisions, we’re here to partner with you to help you gain—and maintain—competitive advantage with efficient, sustainable models at scale. Our expertise in transformation, data science, and change management helps make your business more efficient and effective, improve customer relationships and enhance revenue growth. Instead of focusing on multi-year, resource- and time-intensive platform designs or migrations, we look deeper at your entire value chain to integrate strategies with impact. We use our specialization in analytics, digital interventions, and operations management—alongside deep industry expertise — to deliver solutions that help you outperform the competition. At EXL, it’s all about outcomes—your outcomes—and delivering success on your terms. Share your goals with us and together, we’ll optimize how you leverage data to drive your business forward. For more information, visit www.exlservice.com.

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