---
title: 'Principal Software AI Engineer (R-20013) at Dun & Bradstreet'
canonical: 'https://feeny.ai/job/principal-software-ai-engineer-r-20013-dun-bradstreet-hyderabad-vbw27aq39p84'
type: 'job'
last_seen: '2026-10-31'
---

# Principal Software AI Engineer (R-20013) at Dun & Bradstreet

- **Company:** Dun & Bradstreet
- **Location:** Hyderabad, India
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-10-28
- **Last confirmed live:** 2026-10-31
- **Apply:** https://jobs.lever.co/dnb/73f1d9fd-a35a-46cb-ae0e-f7ad098fcae8

## Job description

Shape the Future with Dun & Bradstreet At Dun & Bradstreet, we believe data has the power to create a better tomorrow. As a global leader in business decisioning data and analytics, we help companies worldwide grow, manage risk, and innovate. Since 1841, businesses have trusted us to turn uncertainty into opportunity. We’re a diverse, global team that values creativity, collaboration, and bold ideas. Are you ready to make an impact and help shape what’s next? Join us! Explore opportunities at dnb.com/careers.

Key Responsibilities:

- Define the architecture and technical direction for enterprise AI/ML and GenAI capabilities, including agentic and conversational AI solutions using platforms and models such as Vertex AI Agent Builder/ADK and Gemini
- Lead the design and delivery of production-grade LLM applications, including embeddings, RAG pipelines, vector database integration, tool use, orchestration, and multi-agent patterns
- Establish reusable AI engineering standards, reference architectures, design patterns, and governance controls for secure, responsible, observable, and maintainable AI solutions
- Provide technical leadership for end-to-end MLOps and CI/CD capabilities supporting model experimentation, evaluation, validation, deployment, monitoring, and lifecycle management
- Architect and guide scalable cloud-native AI services on GCP and Kubernetes using Docker, Infrastructure as Code such as Terraform, and event-driven integration patterns
- Lead the design of data pipelines, APIs, and enterprise integrations that embed AI/ML capabilities into business applications and collaboration platforms
- Define model and system evaluation approaches for quality, safety, latency, reliability, cost, and business effectiveness; guide production monitoring, incident response, root-cause analysis, and prevention
- Partner with Product Owners, Data Scientists, AI Data Engineers, Platform Architects, Security, Risk and Compliance, and application teams to evaluate trade-offs and deliver cost-effective solutions aligned to enterprise standards
- Lead technical design reviews, proofs of concept, and technology evaluations; influence build-versus-buy decisions and the adoption of emerging AI tools and platforms
- Provide training, guidance, and mentorship to engineers and raise engineering capability through code reviews, architecture reviews, knowledge sharing, and best-practice adoption
- Additional duties as assigned

Key Skills:

- Bachelor’s degree in computer science, Engineering, or a related field; master’s degree preferred
- 12+ years of relevant software engineering experience, including substantial experience architecting and deploying production AI/ML solutions at enterprise scale
- Proven technical leadership in the architecture and delivery of large-scale, distributed AI systems across multiple teams or products
- Deep hands-on expertise with agentic AI frameworks and platforms, including Vertex AI Agent Builder / ADK, and large language models such as Gemini
- Expertise in Python application development and APIs, including frameworks such as FastAPI, with strong software design, testing, code review, and version-control practices
- Proven experience designing LLM-based applications, including RAG pipelines, embeddings, vector databases, tool integration, orchestration, prompt and context engineering, and model evaluation
- Deep experience with GenAI frameworks and ecosystems such as LangChain and Hugging Face
- Proven experience designing end-to-end MLOps capabilities using tools such as Vertex AI Pipelines, MLflow, or Kubeflow
- Advanced experience architecting cloud-native solutions on GCP; experience with AWS AI/ML services is a plus
- Proven experience deploying and operating scalable AI/ML services using Docker, Kubernetes, Terraform, CI/CD, observability, and incident-management practices
- Experience defining AI quality, safety, security, privacy, governance, performance, reliability, and cost-management standards for production systems
- Experience with event-driven workflows, enterprise data pipelines, and integrations such as Microsoft Teams and Microsoft Graph API
- Experience with multimodal AI solutions spanning text, image, and audio is preferred
- Ability to influence architecture and engineering decisions across teams and explain complex technical trade-offs to technical and non-technical stakeholders
- Demonstrated ability to mentor senior engineers, lead technical reviews, and establish reusable engineering patterns and standards
- Proficiency in Microsoft Office Suite skills
- Show an ownership mindset in everything you do; be a problem solver, be curious and inspired to take action, be proactive, and seek ways to collaborate and connect with people and teams in support of driving success
- Maintain a continuous growth mindset through relationships with stakeholders, experts, colleagues, and mentors, as well as structured courses and programs
- Where applicable, fluency in English and languages relevant to the working market

All Dun & Bradstreet job postings can be found at https://jobs.lever.co/dnb. Official communication from Dun & Bradstreet will come from an email address ending in @dnb.com.

Notice to Applicants: Please be advised that this job posting page is hosted and powered by Lever, a subsidiary of Employ Inc. Your use of this page is subject to Employ's Privacy Notice and Cookie Policy, which governs the processing of visitor data on this platform.

## About Dun & Bradstreet

## Company Overview
- **One-liner**: Dun & Bradstreet provides business decisioning data, analytics, and a global identity layer (the D-U-N‑S Number) to help companies manage risk, accelerate growth, and operationalize trusted context across sales, finance, compliance, and supply chains.
- **Entity Type**: Public (NYSE: DNB)
- **Headquarters**: Jacksonville, Florida, USA
- **Founded**: 1841
- **Founders**: Not publicly available (historical formation through mergers of Lewis Tappan’s Mercantile Agency and R.G. Dun & Co.)

## Core Business
- **Primary industries**: Information Services, Business Data & Analytics, Credit Risk, Compliance, Supply Chain Management
- **Target customers**: B2B – enterprises, SMBs, financial institutions, government agencies, procurement and risk teams
- **Mission / purpose**: “Since 1841, companies of every size have relied on Dun & Bradstreet to help them manage risk and reveal opportunity.” [dnb.com](https://www.dnb.com/en-us/?cachebust=0.17253344090823353)

## Products & Services
- **D&B Data Cloud**: A governed foundation of verified business identity and continuously updated context, used to enrich CRM, ERP, and AI workflows.
- **D-U-N-S® Number**: A free, globally recognized unique business identifier that establishes a credit profile and unlocks access to suppliers, lenders, and government contracts.
- **D&B Commercial Graph**: A governed data layer delivering traceable, auditable business context for analytics and AI.
- **D&B AI Connectors**: Pre-built integrations that deliver decision-ready business insight into Salesforce, SAP, and other enterprise tools.
- **D&B MCP Server**: Enables AI agents to connect directly to governed business insight for auditability and reliable execution.
- **Risk & Compliance Solutions**: Third-party onboarding, monitoring, and enhanced due diligence.
- **Sales & Marketing Solutions**: Account-based data, lead scoring, and territory insights.
- **Finance Solutions**: Credit risk assessment, cash flow optimization, and financial signals.

## Market Standing
- **Valuation / Market Cap**: Not publicly disclosed in search results (publicly traded on NYSE; market cap can be looked up but not provided in the retrieved data).
- **Key Metric**: Annual revenue of **$2.4B** (latest full fiscal year). Q2 FY2025 (ended June 30, 2025) revenue was **$585.2M** with a net loss of **$33.7M**. [linkedin.com](https://www.linkedin.com/company/dun-&-bradstreet)
- **Notable Investors / Partners**: Parent company **Clearlake Capital Group, L.P.** (majority shareholder). Other institutional investors not listed in the search results.
- **Growth Signals**:
  - Headcount: **4,130 employees** (monthly growth +0.2%)
  - Active job postings: **87** (monthly growth +20.8%, quarterly growth +67.3%)
  - Operating in 28 countries, with data covering many more.
  - Recent emphasis on AI connectors and the MCP server to embed verified business context into agentic workflows.

## Competitive Advantages
- **Persistent Identity (D-U-N-S Number)**: A unique, globally recognized business identifier that provides a single source of truth across systems and use cases, creating a strong switching cost.
- **Longevity & Breadth**: Founded in 1841, the company has accumulated decades of business data and relationships, making it one of the most comprehensive business intelligence providers.
- **Governance & Traceability**: Unlike generic data lakes, the D&B Commercial Graph is designed for auditability, compliance, and AI readiness – a differentiator in regulated industries.
- **Wide Ecosystem Integration**: Native connectors to major platforms (Salesforce, SAP, Tableau, etc.) reduce friction for enterprise adoption.

## Strategic Focus
- **AI as a Context Layer**: Position “verified business context” as the missing link for enterprise AI success, emphasizing governed, traceable data over fragmented inputs.
- **Product Innovation**: Continued development of the MCP Server and AI connectors to enable agentic workflows in procurement, compliance, and sales.
- **Risk & Compliance Expansion**: Deepening capabilities in third-party risk management and enhanced due diligence to meet rising regulatory demands.
- **Data Modernization**: Investing in cloud-native infrastructure and real-time data updates to stay ahead of competitors like Experian and Moody’s.

## Why Work Here
- **Culture & Rating**: Employer rating of **3.8/5** (2,861 reviews on LinkedIn) with strong marks for work-life balance (4.0) and culture (3.7). Compensation scores 3.6 and career development 3.6. [linkedin.com](https://www.linkedin.com/company/dun-&-bradstreet)
- **Work Model**: **Hybrid** – employees typically work on-site **2 days a week** at their Jacksonville HQ or one of 32 global offices. [builtin.com](https://builtin.com/company/dun-bradstreet)
- **Notable Perks**:
  - Performance bonuses and employee discounts
  - Adoption assistance, generous parental leave, and family medical leave
  - Dental, health, and FSA benefits
  - Job training, conferences, and customized development tracks
  - Diverse workforce: talent sourced from top companies (IBM, Oracle, Cognizant, Deloitte, etc.)
- **Technical Environment**: Engineering teams work on large-scale data platforms, AI/ML models, and data pipelines. Open roles include Data Scientists, AI Security Engineers, and Principal Systems Engineers.

## Sources
1. [dnb.com – Company Overview](https://www.dnb.com/en-us/?cachebust=0.17253344090823353)
2. [dnb.com – Careers](https://www.dnb.com/en-us/about/careers.html)
3. [jobs.lever.co – Open Positions](https://jobs.lever.co/dnb)
4. [linkedin.com – Company Profile](https://www.linkedin.com/company/dun-&-bradstreet)
5. [builtin.com – Culture & Perks](https://builtin.com/company/dun-bradstreet)

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