# Senior Enterprise Software Engineer -AI Operations at Wolters Kluwer

Wolters Kluwer is hiring a Senior Enterprise Software Engineer -AI Operations in Chennai, India. Level rates it Builds AI ●●●●; you can [apply on Wolters Kluwer](https://jobsbylevel.com/go/115a491c-fd65-4e1d-9b60-37aa55394863?utm_medium=ai-agent).

AI Level 4, AI centrality 95 out of 100. IND - Chennai, Neville Towers.

## Details

- Company: [Wolters Kluwer](https://jobsbylevel.com/companies/wolters-kluwer)
- AI level: AI Level 4 (score 95 out of 100)
- Location: IND - Chennai, Neville Towers
- Posted: November 12, 2026
- Apply: https://jobsbylevel.com/go/115a491c-fd65-4e1d-9b60-37aa55394863?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=senior-enterprise-software-engineer-ai-operations-at-wolters-kluwer-968f1a

## Prepare for this job

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## Description

About the Role We are seeking an exceptional Senior AI Engineer with 6-8 years of experience to architect and deliver enterprise-grade AI systems at scale, with primary focus on Amazon Bedrock and Microsoft Azure AI Foundry -- the two leading managed cloud AI platforms. This is a staff-level individual contributor position for engineers who can drive technical strategy, mentor cross-functional teams, and translate the latest advances in generative AI into high-impact production systems. You will operate as a principal builder and technical authority across our most ambitious AI initiatives: multi-agent orchestration pipelines, RAG-powered knowledge systems, LLM fine-tuning workflows, and cloud-native AI infrastructure. You will own decisions that reach millions of users and set the engineering benchmark for AI excellence across the organization. This role intentionally avoids SageMaker-centric workflows in favor of the latest serverless and managed AI services -- Amazon Bedrock AgentCore, Amazon Nova, Amazon S3 Vectors, Microsoft Foundry, and Azure AI Agent Service -- enabling faster iteration, lower infrastructure overhead, and access to frontier models. Key Responsibilities Technical Leadership & AI Architecture Own end-to-end architecture of cloud-native AI systems on AWS and Azure, from raw data ingestion through LLM serving, evaluation, and continuous monitoring. Establish AI engineering standards, model governance frameworks, and cloud design patterns adopted across multiple product teams. Lead critical cross-platform design decisions: when to use AWS Bedrock vs. Azure AI Foundry, which foundation model best fits performance and cost constraints, and when to fine-tune vs. prompt-engineer. Evaluate and rapidly prototype with emerging AWS and Azure AI capabilities (Amazon Nova 2, Bedrock Reinforcement Fine-Tuning, Azure GPT-5-Codex, Foundry Agent Service) to keep the organization at the frontier. Drive technical design reviews, architecture critiques, and risk assessments for high-stakes AI deployments. AWS Amazon Bedrock & Generative AI Engineering Architect enterprise applications using Amazon Bedrock as the primary LLM serving and orchestration platform -- leveraging the full model catalog including Amazon Nova 2 (Lite, Pro, Sonic, Omni), Anthropic Claude, Mistral Large 3, and Amazon Bedrock Marketplace models. Build production multi-agent systems using Amazon Bedrock AgentCore: design agent boundaries with Policy controls, implement episodic Memory for long-horizon reasoning, and configure AgentCore Gateway for secure tool integrations with Salesforce, Slack, and internal APIs. Implement browser-based workflow automation agents with Amazon Nova Act, achieving 90%+ task reliability for form filling, data extraction, QA testing, and enterprise UI automation workflows. Design and deploy RAG pipelines using Amazon Bedrock Knowledge Bases with Amazon S3 Vectors as the primary vector store -- supporting up to 2 billion vectors per index with 100ms query latencies at up to 90% lower cost than specialized vector databases. Apply Amazon Bedrock Reinforcement Fine-Tuning for domain-specific model customization, achieving up to 66% accuracy gains over base models without requiring labeled datasets or deep ML expertise. Leverage Amazon Bedrock Model Distillation to create task-specific models that run up to 500% faster and cost 75% less, with minimal accuracy trade-off. Implement Amazon Bedrock Intelligent Prompt Routing and Prompt Caching to reduce inference costs by up to 30% while maintaining response quality. Apply Amazon Bedrock Guardrails for responsible AI enforcement: content filtering, hallucination prevention, PII redaction, and compliance controls across all production LLM endpoints. Develop and manage Kiro-based agentic development workflows: context-aware, session-persistent autonomous agents for coding and operational task automation. AZURE Microsoft Foundry & Azure AI Engineering Build and deploy intelligent

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