GenAI Applications Development Manager
Role Overview<\/b>
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We are seeking an experienced <\/span>GenAI Applications Development Manager<\/b> to lead end\-to\-end development and delivery of Generative AI products. This role bridges AI architecture, product development, and engineering execution. You will collaborate with <\/span>AI Architects, Solution Architects, AI/ML Engineers, Prompt Engineers, and Full Stack Developers<\/b> to build production\-ready, scalable AI applications.
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Requirements<\/h3>
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Requirements<\/h3>Key Responsibilities<\/b>
<\/div>GenAI/AI Program & Delivery Management<\/b>
<\/div>- Lead full lifecycle of GenAI application development: ideation, architecture, development, testing, deployment, and optimization
<\/li> - Partner with AI Architects and Solution Architects to translate business requirements into scalable GenAI solutions
<\/li> - Define product roadmaps, sprint plans, milestones, and delivery timelines for GenAI initiatives
<\/li> - Oversee development of LLM\-powered applications including RAG systems, conversational AI, and AI agents
<\/li> - Drive agile delivery with iterative development cycles and rapid prototyping
<\/li><\/ul>Team Leadership & Collaboration<\/b>
<\/div>- Lead cross\-functional teams: AI/ML Engineers, Prompt Engineers, Full Stack Developers, DevOps/MLOps Engineers, and QA Engineers
<\/li> - Collaborate with AI Architects on system design, model selection, and integration patterns
<\/li> - Foster innovation, experimentation, and continuous learning in AI/ML technologies
<\/li> - Build and scale high\-performing AI development teams; drive hiring and capability development
<\/li><\/ul>GenAI Technology & Platform Oversight<\/b>
<\/div>- Guide selection and implementation of LLMs, embedding models, and AI frameworks
<\/li> - Oversee prompt engineering strategies, RAG architectures, and vector database implementations
<\/li> - Manage AI/ML infrastructure: cloud platforms (Azure, AWS, GCP), GPU resources, and model serving
<\/li> - Drive MLOps practices: CI/CD pipelines, model versioning, monitoring, and observability
<\/li><\/ul>Stakeholder Communication & Reporting<\/b>
<\/div>- Communicate project progress, risks, and outcomes to senior leadership
<\/li> - Translate complex AI/ML concepts into business\-focused language for executive audiences
<\/li> - Present product demos, technical architectures, and ROI analyses to stakeholders
<\/li><\/ul>Required Skills & Qualifications<\/b>
<\/div>Experience<\/b>
<\/div>- 8+ years in software development, AI/ML, or technology product management
<\/li> - 4+ years leading AI/ML or GenAI development teams and programs
<\/li> - Proven track record delivering production\-grade AI applications
<\/li><\/ul>Technical Knowledge<\/b>
<\/div>- Strong understanding of LLMs (GPT, Claude, Llama), prompt engineering, RAG architectures, and AI agents
<\/li> - Proficiency in AI/ML platforms: LangChain, LlamaIndex, Hugging Face, OpenAI/Azure OpenAI APIs
<\/li> - Understanding of full stack development: Python, JavaScript/TypeScript, REST APIs, microservices
<\/li> - Familiarity with cloud platforms (Azure, AWS, GCP) and MLOps tooling
<\/li><\/ul>Leadership & Soft Skills<\/b>
<\/div>- Excellent communication skills; ability to influence technical and business stakeholders
<\/li> - Strong product thinking with focus on user experience and business outcomes
<\/li> - Proven ability to build, mentor, and scale high\-performing technical teams
<\/li><\/ul>Education<\/b>
<\/div>- Bachelor's or Master's degree in Computer Science, Engineering, AI/ML, Data Science, or related field
<\/li> - AI/ML or Product Management certifications are a plus
<\/li><\/ul>Nice to Have<\/b>
<\/div>- Prior hands\-on experience as a software engineer, ML engineer, or data scientist
<\/li> - Experience building AI products in regulated industries (healthcare, finance)
<\/li> - Knowledge of agentic AI systems and multi\-agent architectures
<\/li> - Experience with enterprise AI platforms (Azure AI, AWS SageMaker, Databricks)
<\/li><\/ul>What This Role Offers<\/b>
<\/div>- Lead cutting\-edge GenAI product development with high visibility to senior leadership
<\/li> - Ownership of innovative AI products from inception to production
<\/li> - Work with talented AI architects, engineers, and domain experts
<\/li> - Continuous learning and growth in the rapidly evolving GenAI space
<\/li><\/ul>
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GenAI/AI Program & Delivery Management<\/b>
<\/div>
<\/div>
- Lead full lifecycle of GenAI application development: ideation, architecture, development, testing, deployment, and optimization
<\/li> - Partner with AI Architects and Solution Architects to translate business requirements into scalable GenAI solutions
<\/li> - Define product roadmaps, sprint plans, milestones, and delivery timelines for GenAI initiatives
<\/li> - Oversee development of LLM\-powered applications including RAG systems, conversational AI, and AI agents
<\/li> - Drive agile delivery with iterative development cycles and rapid prototyping
<\/li><\/ul>Team Leadership & Collaboration<\/b>
<\/div>- Lead cross\-functional teams: AI/ML Engineers, Prompt Engineers, Full Stack Developers, DevOps/MLOps Engineers, and QA Engineers
<\/li> - Collaborate with AI Architects on system design, model selection, and integration patterns
<\/li> - Foster innovation, experimentation, and continuous learning in AI/ML technologies
<\/li> - Build and scale high\-performing AI development teams; drive hiring and capability development
<\/li><\/ul>GenAI Technology & Platform Oversight<\/b>
<\/div>- Guide selection and implementation of LLMs, embedding models, and AI frameworks
<\/li> - Oversee prompt engineering strategies, RAG architectures, and vector database implementations
<\/li> - Manage AI/ML infrastructure: cloud platforms (Azure, AWS, GCP), GPU resources, and model serving
<\/li> - Drive MLOps practices: CI/CD pipelines, model versioning, monitoring, and observability
<\/li><\/ul>Stakeholder Communication & Reporting<\/b>
<\/div>- Communicate project progress, risks, and outcomes to senior leadership
<\/li> - Translate complex AI/ML concepts into business\-focused language for executive audiences
<\/li> - Present product demos, technical architectures, and ROI analyses to stakeholders
<\/li><\/ul>Required Skills & Qualifications<\/b>
<\/div>Experience<\/b>
<\/div>- 8+ years in software development, AI/ML, or technology product management
<\/li> - 4+ years leading AI/ML or GenAI development teams and programs
<\/li> - Proven track record delivering production\-grade AI applications
<\/li><\/ul>Technical Knowledge<\/b>
<\/div>- Strong understanding of LLMs (GPT, Claude, Llama), prompt engineering, RAG architectures, and AI agents
<\/li> - Proficiency in AI/ML platforms: LangChain, LlamaIndex, Hugging Face, OpenAI/Azure OpenAI APIs
<\/li> - Understanding of full stack development: Python, JavaScript/TypeScript, REST APIs, microservices
<\/li> - Familiarity with cloud platforms (Azure, AWS, GCP) and MLOps tooling
<\/li><\/ul>Leadership & Soft Skills<\/b>
<\/div>- Excellent communication skills; ability to influence technical and business stakeholders
<\/li> - Strong product thinking with focus on user experience and business outcomes
<\/li> - Proven ability to build, mentor, and scale high\-performing technical teams
<\/li><\/ul>Education<\/b>
<\/div>- Bachelor's or Master's degree in Computer Science, Engineering, AI/ML, Data Science, or related field
<\/li> - AI/ML or Product Management certifications are a plus
<\/li><\/ul>Nice to Have<\/b>
<\/div>- Prior hands\-on experience as a software engineer, ML engineer, or data scientist
<\/li> - Experience building AI products in regulated industries (healthcare, finance)
<\/li> - Knowledge of agentic AI systems and multi\-agent architectures
<\/li> - Experience with enterprise AI platforms (Azure AI, AWS SageMaker, Databricks)
<\/li><\/ul>What This Role Offers<\/b>
<\/div>- Lead cutting\-edge GenAI product development with high visibility to senior leadership
<\/li> - Ownership of innovative AI products from inception to production
<\/li> - Work with talented AI architects, engineers, and domain experts
<\/li> - Continuous learning and growth in the rapidly evolving GenAI space
<\/li><\/ul>
<\/div><\/span>
- Lead cutting\-edge GenAI product development with high visibility to senior leadership
- Prior hands\-on experience as a software engineer, ML engineer, or data scientist
- Bachelor's or Master's degree in Computer Science, Engineering, AI/ML, Data Science, or related field
- Excellent communication skills; ability to influence technical and business stakeholders
- Strong understanding of LLMs (GPT, Claude, Llama), prompt engineering, RAG architectures, and AI agents
- 8+ years in software development, AI/ML, or technology product management
- Communicate project progress, risks, and outcomes to senior leadership
- Guide selection and implementation of LLMs, embedding models, and AI frameworks
- Lead cross\-functional teams: AI/ML Engineers, Prompt Engineers, Full Stack Developers, DevOps/MLOps Engineers, and QA Engineers