GEN AI Senior Manager
Tredence Inc.
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Job summary
Tredence Inc. is seeking an experienced Senior Manager – Generative AI to lead the design, development, and deployment of enterprise-scale AI solutions.
The role blends technology leadership, solution architecture, stakeholder management, and people leadership to drive GenAI strategy across industries. You will partner with business leaders, data scientists, architects, engineering teams, and clients to translate challenges into scalable AI solutions, leveraging LLMs, RAG, and cloud-native tech.
Qualifications
- Bachelor’s or Master’s degree in CS/AI/DS or related field.
- 12–18+ years in Analytics, Data Science, AI/ML, or Software Engineering.
- 5+ years of leadership experience managing large technical teams.
- 3+ years of hands-on experience delivering Generative AI solutions in production environments.
Responsibilities
- Define and drive Generative AI roadmap and innovation strategy.
- Lead AI transformation initiatives for clients and internal stakeholders.
- Collaborate with executives to align AI investments with business goals.
- Design enterprise-grade GenAI solutions using LLMs and foundation models.
- Drive end-to-end delivery of AI programs from discovery to production deployment.
- Build scalable, secure, and responsible AI systems.
- Establish governance, privacy, and compliance standards.
Skills
Education
Tools
Job description
We are seeking an experienced Senior Manager – Generative AI to lead the design, development, and deployment of enterprise-scale AI and Generative AI solutions. The role requires a strong blend of technology leadership, solution architecture, stakeholder management, and people leadership. The ideal candidate will drive GenAI strategy, build high-performing teams, and deliver innovative AI-driven business outcomes across industries.
This role will partner closely with business leaders, data scientists, architects, engineering teams, and clients to translate business challenges into scalable AI solutions leveraging Large Language Models (LLMs), Agentic AI, RAG frameworks, Machine Learning, and cloud-native technologies.
- Define and drive the organization's Generative AI roadmap and innovation strategy.
- Identify high-impact business opportunities for GenAI adoption.
- Lead AI transformation initiatives for clients and internal stakeholders.
- Collaborate with executive leadership to align AI investments with business goals.
- Act as a thought leader and evangelist for AI/GenAI capabilities.
- Design enterprise-grade GenAI solutions using LLMs and foundation models.
- Lead architecture reviews and establish AI engineering best practices.
- Drive end-to-end delivery of AI programs from discovery through production deployment.
- Build scalable, secure, and responsible AI systems.
- Ensure adherence to governance, privacy, and compliance standards.
We are seeking an experienced Senior Manager – Generative AI to lead the design, development, and deployment of enterprise-scale AI and Generative AI solutions. The role requires a strong blend of technology leadership, solution architecture, stakeholder management, and people leadership. The ideal candidate will drive GenAI strategy, build high-performing teams, and deliver innovative AI-driven business outcomes across industries.
This role will partner closely with business leaders, data scientists, architects, engineering teams, and clients to translate business challenges into scalable AI solutions leveraging Large Language Models (LLMs), Agentic AI, RAG frameworks, Machine Learning, and cloud-native technologies.
- Define and drive the organization's Generative AI roadmap and innovation strategy.
- Identify high-impact business opportunities for GenAI adoption.
- Lead AI transformation initiatives for clients and internal stakeholders.
- Collaborate with executive leadership to align AI investments with business goals.
- Act as a thought leader and evangelist for AI/GenAI capabilities.
- Design enterprise-grade GenAI solutions using LLMs and foundation models.
- Lead architecture reviews and establish AI engineering best practices.
- Drive end-to-end delivery of AI programs from discovery through production deployment.
- Build scalable, secure, and responsible AI systems.
- Ensure adherence to governance, privacy, and compliance standards.
- Lead implementation of:
- Retrieval-Augmented Generation (RAG)
- Agentic AI Systems
- AI Copilots
- Multi-Agent Frameworks
- Conversational AI Solutions
- Enterprise Search Solutions
- Knowledge Management Platforms
- Evaluate and integrate models from:
- OpenAI
- Azure OpenAI
- Anthropic Claude
- Google Gemini
- Meta Llama
- Mistral
- Build, mentor, and manage teams of Data Scientists, ML Engineers, AI Engineers, and Solution Architects.
- Drive hiring, capability development, performance management, and career growth initiatives.
- Establish a culture of innovation, collaboration, and continuous learning.
- Provide technical coaching and architectural guidance.
- Engage with CXOs and business leaders to understand strategic priorities.
- Conduct AI workshops, assessments, and executive presentations.
- Lead solutioning for RFPs, proposals, and pre-sales opportunities.
- Drive stakeholder communication and program governance.
- Establish frameworks for:
- AI Governance
- Model Risk Management
- LLM Evaluation
- Prompt Engineering Standards
- Responsible AI Practices
- Monitor solution effectiveness and continuously optimize AI systems.
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, Mathematics, Statistics, or related field.
- 12-18+ years in Analytics, Data Science, AI/ML, or Software Engineering.
- 5+ years of leadership experience managing large technical teams.
- 3+ years of hands‑on experience delivering Generative AI solutions in production environments.
- Proven track record of leading enterprise‑scale AI transformation programs.
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- Fine‑Tuning & Model Optimization
- Prompt Engineering
- Agentic AI
- Knowledge Graphs
- AI Copilots
- Vector Databases
- Supervised and Unsupervised Learning
- Deep Learning
- NLP
- Recommendation Systems
- MLOps
- Python
- SQL
- PySpark
- APIs & Microservices
- LangChain
- LangGraph
- LlamaIndex
- AutoGen
- CrewAI
- Semantic Kernel
- Hugging Face
- MLflow
- Microsoft Azure
- Azure OpenAI
- AWS Bedrock
- Google Vertex AI
- Databricks
- Snowflake
- Synapse
- Fabric
- Hadoop Ecosystem
- Docker
- Kubernetes
- CI/CD Pipelines
- Model Monitoring
- GitHub / Azure DevOps
- Strategic Thinking
- Executive Presence
- Client Relationship Management
- Stakeholder Management
- Team Building & Coaching
- Business Acumen
- Decision Making
- Innovation Mindset
- Problem Solving
- Change Management
- Experience leading GenAI Centers of Excellence (CoE).
- Experience in consulting, analytics services, or data-driven product organizations.
- Azure AI Engineer, Azure Data Scientist, AWS ML Specialty, or equivalent certifications.
- Exposure to Responsible AI and AI Governance frameworks.
- Experience working with Fortune 500 clients.
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