Note: The job is a remote job and is open to candidates in USA. Dice is seeking a strategic GenAI Product Engineering Lead to drive the design and delivery of an enterprise-grade AI platform on Microsoft Azure. The role involves leading a multidisciplinary team to develop scalable and secure solutions that enhance business operations and provide exceptional value to clients.
Responsibilities
- Lead, mentor, and grow a high-performing engineering team, fostering a culture of innovation, accountability, and continuous improvement
- Establish and enforce engineering best practices, focusing on code quality, reliability, and operational efficiency
- Set technical direction and ensure alignment with enterprise goals and standards
- Architect scalable, secure, and resilient AI systems on Azure (and other cloud environments as needed), working with Large Language Models (LLMs), and collaborating with cross-functional teams to integrate AI into products and processes. A strong technical foundation in areas like Python, AI/ML frameworks, and cloud platforms, combined with project management and leadership skills, are essential for this role
- Define Power Platform apps from end-to-end, including backend data pipelines
- Define and enforce architectural standards, including microservices, event-driven design, and API-first principles
- Architect multi-tenant B2B environments with tenant-aware data partitions using Cosmos DB and Azure AD B2C/Entra ID to ensure data, security, and cost isolation
- Build per-tenant vector stores, knowledge bases, and connectors to support customer-specific document ingestion and retrieval
- Implement telemetry, metering, and consumption-based billing dashboards to track tenant-level usage and optimize resource allocation
- Design and implement advanced GenAI solutions, including agent-based systems for automation, orchestration, and intelligent workflows
- Integrate large language models (LLMs), Retrieval-Augmented Generation (RAG), and custom agents with business processes and user-facing applications
- Lead design using frameworks such as Semantic Kernel, LangChain, AutoGen, or CrewAI to build orchestration among multiple specialized agents
- Lead domain-specific fine-tuning and adaptation of large language models using Azure OpenAI Service or third-party frameworks (e.g., Tinker AI, LoRA, PEFT, or Delta Tuning)
- Design modular fine-tuning workflows to create tenant-aware or task-specific models that enhance personalization while maintaining shared governance and security
- Implement automated retraining and evaluation loops to continuously improve response accuracy, tone, and compliance across tenants
- Design agent toolkits that connect external APIs, databases, and Power Platform components for automated workflows
- Oversee model evaluation, tuning, and continuous improvement cycles using reinforcement learning from human feedback (RLHF) or synthetic data augmentation
- Establish model-drift detection and retraining triggers to sustain model performance across customer domains
- Track usage analytics to measure model performance, accuracy, and user engagement
- Govern token usage, compute allocation, and cost optimization strategies using Azure Cost Management
- Manage versioning of models, prompts, and embeddings to ensure reproducibility, auditability, and traceability as part of the ongoing GenAI lifecycle operations
- Design, develop, and maintain robust, scalable, and secure full-stack web applications
- Build dynamic and responsive user interfaces using React, TypeScript, and modern state management libraries
- Architect and implement scalable backend services and RESTful APIs using Python (with frameworks like FastAPI or Flask) and caching technologies like Redis
- Design and manage data models and interact with both relational (SQL) and NoSQL databases (e.g., Cosmos DB)
- Collaborate with citizen developers and business stakeholders to enable rapid app development using Power Apps, Power Automate, and Power BI
- Ensure seamless integration between custom Azure services and Power Platform components
- Lead the design and implementation of robust data ingestion, transformation, and processing pipelines using Azure Data Factory, Databricks, Synapse, or equivalent
- Ensure data quality, governance, and compliance with enterprise and regulatory standards
- Develop secure pipelines for fine-tuning data preparation, ensuring data labeling, anonymization, and quality scoring to meet Responsible AI standards
- Leverage Azure ML pipelines or Databricks workflows to automate dataset curation and model retraining schedules
- Optimize compute resources using Azure Functions, AKS, and serverless architectures for cost-effective, high-performance workloads
- Implement auto-scaling, load balancing, and failover strategies for mission-critical applications
- Champion security best practices, including identity management, data protection, and compliance (e.g., SOC2, GDPR)
- Establish monitoring, alerting, and incident response protocols for platform reliability and operational excellence
- Act as a technical liaison between engineering, product, business, and executive teams
- Communicate complex technical concepts clearly to non-technical stakeholders
Skills
- Proven experience leading engineering teams in building enterprise-grade platforms on Azure
- Deep expertise in cloud architecture, distributed systems, and scalable frameworks
- Advanced proficiency in GenAI, agent-based systems, and LLMs. Understanding of agent frameworks (e.g., LangChain, Semantic Kernel) and orchestration tools
- Strong background in data engineering, including ETL, data lakes, and real-time processing
- Demonstrated ability to design secure, compliant, and reliable cloud solutions
- Generative AI Expert with: Direct experience integrating LLMs (e.g., Azure OpenAI), developing RAG workflows, and using vector databases (e.g., Azure AI Search)
- Strong proficiency in languages like Python, with experience in AI/ML frameworks such as TensorFlow, PyTorch, or Keras
- Experience with LLMs, prompt engineering, agentic flows, and foundational AI techniques
- Experience with cloud-native development (e.g., AWS, Azure) and building scalable microservices
- Strong fundamentals in software engineering, system architecture, and lifecycle management
- Knowledge of enterprise security, compliance, and governance standards
- Track record of delivering large-scale, multi-tenant platforms
- Excellent leadership, communication, and stakeholder management skills
- Experience working in Agile, Scrum, or Kanban environments
- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience
- Experience building and deploying fine-tuned or adapted LLMs using tools such as Tinker AI, Azure AI Studio, Hugging Face, or MosaicML
- Knowledge of parameter-efficient tuning methods (LoRA, PEFT, QLoRA) and prompt-based adaptation techniques
- Understanding of API Gateway & Identity federation (Azure API Management, Entra ID multi-tenant apps)
- Experience with Azure Data Factory, Synapse, Databricks, and Power Platform (Power Apps, Power Automate, Power BI)
- SaaS Experience: Experience building and supporting multi-tenant SaaS applications
- Azure Ecosystem: Expertise with specific Azure services such as Azure AI Services, Azure App Services, Azure Functions, Azure DevOps, and Azure Kubernetes Service (AKS)
- Infrastructure as Code (IaC): Experience using IaC tools like Bicep or Terraform to manage cloud resources
- Containerization: Proficiency with Docker and container orchestration tools like Kubernetes
- Modern Frontend Tooling: Experience with TypeScript and state management libraries (e.g., Redux, Zustand)
Benefits
- Medical, dental, vision, life, disability, and other insurance plans that offer an optional layer of financial protection
- ESPP (employee stock purchase program)
- 401K program which allows you to contribute typically within 30 days of starting, with a company match after 12 months of tenure
- HSA (Health Savings Account on the HDHP plan)
- SupportLinc Employee Assistance Program (EAP) with up to 8 free counseling sessions
- Corporate discount savings program and other discounts
- On-demand training program
- Access to certification prep and a library of technical and leadership courses/books/seminars once you have 6+ months of tenure
- Certification discounts and other perks to associations that include CompTIA and IIBA
- Dedicated customer service team for our Consultants that can address questions around benefits and other resources
- Certified Career Coach
- 'Welcome Packet' as well, which an Everforth Apex team member can provide
Company Overview
Dice is a job-searching platform for technology professionals. It is a sub-organization of DHI Group. It was founded in 1990, and is headquartered in Santa Clara, California, USA, with a workforce of 201-500 employees. Its website is http://www.dice.com.