Senior GenAI Enterprise Architect

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🕒 July 10

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EXL

WebsiteLinkedInAll Job Openings

10,000+ employees

🏥 Healthcare

🛡️ Insurance

📦 Logistics

💰 $2M Venture Round on 2015-01

Healthcare • Insurance • Logistics

EXL is a business consulting and services firm that focuses on leveraging data to enhance business operations and decision-making. With a strong emphasis on collaboration and adaptability, EXL partners with organizations to address their unique needs and culture while integrating data science and technology solutions. The company's areas of expertise include operations management, decision analytics, digital transformation, and various industries such as healthcare, finance, and insurance. EXL's mission is to help clients drive business evolution and maintain competitive advantage through tailored solutions and effective use of data.

📋 Description

• Architect end-to-end Generative AI systems by operationalizing the 7-layer AI architecture (Data Sources, Preprocessing, Model Selection, Orchestration, Inference, Integration, and Application). • Evaluate and select cutting-edge commercial (e.g., GPT-4) and open-source models, and fine-tune models for domain-specific use cases. • 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. • 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. • Collaborate with stakeholders to map business challenges to AI solutions and establish AI governance frameworks. • Act as the primary onshore technical liaison, facilitating client workshops, requirements gathering, and translating business pain points into technical AI blueprints.

🎯 Requirements

• 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. • Deep knowledge of NLP, Python, deep learning frameworks (PyTorch/TensorFlow), and orchestration tools (LangChain, Autogen). • Extensive hands-on experience with AI services on AWS, Azure, or GCP. Expertise in vector databases (e.g., Pinecone, Milvus) and embedding techniques. • Exceptional client-facing communication skills; proven ability to present complex technical concepts to business stakeholders.