Job Description : AI Manager - Agentic AI & Generative AI

We are looking for an experienced AI Manager - Agentic AI & Generative AI to lead the design, development, and deployment of intelligent AI agent systems, LLM-based applications, and autonomous workflow solutions for enterprise applications.

The ideal candidate will combine strong technical expertise in AI/ML, Agentic AI, and Generative AI with leadership capabilities to drive AI solution architecture, manage engineering teams, and deliver scalable, secure, and production-ready enterprise AI solutions.

Key Responsibilities :

- Lead the design, architecture, development, and deployment of Agentic AI systems, LLM-based applications, and autonomous workflows.

- Drive the implementation of multi-agent architectures to automate complex enterprise business processes.

- Define technical strategies and best practices for LLM applications, RAG pipelines, prompt engineering, and agent orchestration.

- Oversee the development of AI solutions using Python and frameworks such as LangChain, LlamaIndex, Transformers, and PyTorch.

- Lead the adoption and integration of cloud AI services, including Azure OpenAI, AWS Bedrock, and Google Vertex AI.

- Guide the integration of LLMs with enterprise applications, APIs, databases, vector stores, and knowledge graphs.

- Ensure AI solutions meet requirements for scalability, performance, reliability, security, and responsible AI implementation.

- Oversee deployment and monitoring of AI models and agents across development, staging, and production environments.

- Establish evaluation frameworks to assess AI accuracy, response quality, hallucinations, performance, and business outcomes.

- Lead, mentor, and develop AI/ML engineers and technical teams, fostering engineering excellence and continuous learning.

- Collaborate with business stakeholders, product teams, architects, and engineering leaders to translate business needs into AI solutions.

- Manage project planning, technical delivery, resource allocation, risks, dependencies, and stakeholder expectations.

- Communicate AI capabilities, limitations, delivery timelines, and technical risks to senior leadership and business stakeholders.

- Drive continuous innovation and identify opportunities to leverage Agentic AI and Generative AI across enterprise workflows.

Required Skills & Qualifications :

- 10-15 years of overall experience in AI/ML engineering, software engineering, or enterprise technology, with substantial hands-on experience in AI/ML.

- Proven experience leading AI/ML engineering teams and delivering enterprise AI solutions.

- Strong understanding of Large Language Models (LLMs), Generative AI, Agentic AI, and multi-agent architectures.

- Experience designing and implementing end-to-end Agentic AI solutions, preferably with at least three complete implementations.

- Strong proficiency in Python and AI/ML frameworks such as LangChain, LlamaIndex, Transformers, and PyTorch.

- Hands-on experience with cloud AI platforms such as Azure OpenAI, AWS Bedrock, or Google Vertex AI.

- Expertise in RAG architecture, vector databases, embeddings, knowledge graphs, and enterprise data integration.

- Experience integrating LLMs with enterprise systems, APIs, and external applications.

- Experience deploying and operating AI solutions in production environments.

- Strong knowledge of AI evaluation, monitoring, guardrails, security, and responsible AI practices.

- Excellent leadership, stakeholder management, communication, and problem-solving skills.

Good to Have :

- Experience with MLOps, CI/CD, containerization, Kubernetes, and cloud-native architectures.

- Knowledge of LLM observability, model evaluation frameworks, and AI governance.

- Experience driving enterprise AI strategy, proof of concepts, and large-scale AI transformation initiatives.

- Relevant cloud, AI/ML, or Generative AI certifications.