[Remote] Gen AI Engineer Lead

Remote · USA Full-time New today

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.

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