AI Program Manager / AI Engineering Manager

KR Elixir; Bengaluru; Hybrid; INR 4,000,000 - 8,000,000; Full time

Job summary

KR Elixir in Bengaluru is seeking an experienced AI Program Manager / AI Engineering Manager with 12-17 years to lead enterprise Generative and Agentic AI engagements. You will drive delivery from initiation to production, coordinating with clients, AI engineers, architects, and cloud teams to ensure successful AI initiatives.

The role emphasizes Agentic AI delivery, AI engineering, cloud platforms, governance, and exceptional communication with senior stakeholders while mentoring

Qualifications

• Proven experience delivering Agentic AI and Generative AI solutions at enterprise scale.
• Strong leadership across multi-disciplinary teams and client-facing delivery.
• Experience with AI governance, security, and responsible AI practices.

Responsibilities

• Lead end-to-end delivery of Agentic AI and Generative AI engagements.
• Own scope, timelines, budgets, risks, dependencies, and milestones.
• Drive AI engineering delivery practices incl. CI/CD, observability and production readiness.
• Manage client relationships and executive communications.
• Mentor AI engineers and engineering managers across multiple workstreams.

Skills

AI program management

Delivery leadership

Client stakeholder engagement

AI engineering

Cloud platforms

MLOps & CI/CD

Tools

LangChain

LangGraph

AutoGen

CrewAI

Semantic Kernel

LlamaIndex

Job description

About the Role

We are looking for an experienced AI Program Manager / AI Engineering Manager with 12 - 17 years of experience to lead the delivery of complex, enterprise-scale Generative AI and Agentic AI engagements for clients.

The role is responsible for managing AI engineering programs across the full delivery lifecycle from technical initiation and planning through development, integration, deployment and production. The individual will work closely with client stakeholders, AI/ML engineers, software engineers, architects, cloud teams and internal delivery leadership to ensure successful execution of AI initiatives.

The ideal candidate will have strong and demonstrated experience in Agentic AI solution delivery, combined with a solid understanding of AI engineering, enterprise architecture, cloud platforms and technology delivery. They should also be an exceptional communicator and relationship builder, capable of confidently engaging with senior client stakeholders and effectively managing diverse internal teams.

Delivery Leadership

• Lead the end-to-end delivery of Agentic AI and Generative AI engagements for enterprise clients, from technical initiation through development, deployment and production.
• Own delivery across scope, timelines, resources, budgets, dependencies, risks, issues and delivery milestones.
• Manage delivery governance including project status, RAID management, dependency tracking, milestone reporting, steering committee updates and executive communication.
• Establish and maintain effective AI engineering delivery practices including Agile execution, CI/CD, testing, observability, monitoring, release management and production readiness.

Client & Stakeholder Engagement

• Act as a key client-facing delivery leader, establishing strong relationships and maintaining regular communication with client stakeholders throughout the engagement.
• Build and maintain trusted relationships with senior client stakeholders, understand their priorities and expectations, and ensure alignment throughout the delivery lifecycle.
• Manage stakeholder expectations effectively, ensuring transparency around scope, timelines, risks, technical constraints and delivery outcomes.
• Comfortable leading client meetings, steering committees, technical discussions, status reviews and executive presentations.

AI & Technical Delivery

• Drive implementation of Agentic AI solutions, including AI agents, multi-agent workflows, AI orchestration, tool integrations, RAG-based solutions and AI-enabled enterprise workflows.
• Provide technical delivery leadership across LLMs, RAG, embeddings, vector databases, prompt engineering, tool/function calling, AI agents, model integration and orchestration frameworks.
• Work with architecture and engineering teams to translate solution designs into well-planned and executable engineering workstreams.
• Identify technical dependencies, integration challenges and delivery risks and drive their timely resolution.
• Oversee integration of AI solutions with enterprise applications, APIs, data platforms and existing technology ecosystems.
• Ensure project delivery adheres to appropriate security, architecture, governance, compliance and responsible AI standards.

Team Leadership

• Lead and manage cross-functional AI and engineering teams across multiple workstreams.
• Manage team capacity, allocation, priorities and delivery commitments across multiple AI workstreams.
• Mentor and develop AI engineers, technical leads and engineering managers, promoting strong engineering and delivery practices.
• Drive a culture of delivery accountability, technical excellence, continuous improvement and client-centricity.

Preferred Experience

• Multiple successful implementations of Agentic AI solutions in enterprise environments.
• Experience with multi-agent architectures, AI orchestration frameworks (e.g. AutoGen, CrewAI, LangGraph), autonomous AI workflows, enterprise copilots or AI-powered workflow automation.
• Experience integrating AI solutions with enterprise applications, APIs, data platforms and complex technology ecosystems.
• Experience delivering AI solutions within highly regulated or security-sensitive enterprise environments.
• Experience with AI governance, responsible AI frameworks, model evaluation, observability and production monitoring.
• Familiarity with MLOps practices, model deployment pipelines, and AI observability tooling (e.g. LangSmith, Weights & Biases, Helicone).
• Experience managing large, distributed engineering teams and multiple concurrent AI workstreams.
• Experience with cloud migration, modernization and cloud-native transformation.
• Experience in technology consulting, IT services or client-facing enterprise delivery environments.

AI & Technical Knowledge

• Strong understanding of Agentic AI architectures, AI agents, multi-agent systems, LLM-based applications, RAG, embeddings, vector databases, tool/function calling and AI orchestration.
• Hands-on familiarity with AI/Agentic frameworks and tooling including LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel, LlamaIndex, and similar orchestration frameworks.
• Experience with LLM providers and APIs including OpenAI, Azure OpenAI, Anthropic Claude, Google Gemini, AWS Bedrock and/or open-source models.
• Familiarity with vector databases such as Pinecone, Weaviate, Chroma, pgvector or Azure AI Search.
• Understanding of prompt engineering, function/tool calling, agent memory, planning and reasoning patterns.
• Strong understanding of cloud platforms such as AWS, Microsoft Azure and GCP, including core services relevant to AI/ML workloads (compute, storage, networking, managed AI services, identity and security).
• Proven experience leading or contributing to cloud migration, application modernization and cloud-native transformation programs, preferably in the context of AI or data platform delivery.
• Strong understanding of modern software engineering lifecycle, APIs, CI/CD, DevOps, testing, monitoring and production delivery practices.

Program & Delivery Skills

• Strong program delivery capabilities covering planning, resource management, risk management, dependency management, governance and execution.
• Ability to understand and evaluate AI solution architecture, technical designs, engineering dependencies and integration considerations.
• Proven experience leading and mentoring AI/engineering teams and technical leads.