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▷ [3 Days Left] Director, AI Engineering
KPMG Delivery Network (KDN)India10 hours ago
Job descriptionOwn the engineering roadmap for the KDN Agent Factory, ensuring agent orchestration, safety, and lifecycle governance. Integrate AI Foundry pipelines with marketplace for Bring-Your-Own-Agent (BYOA) and Managed AI Service capabilities. Oversee the continuous delivery of secure, portable agents across Azure Stack, AWS Bedrock, and GCP Vertex. Collaborate with global COEs to embed explainability, observability, and compliance automation into all releases. Partner with Data Engineering teams to evolve Data Ocean as the single source of truth for model training and inference data. Ensure AI-native integrations with SAP, Oracle, Workday, ServiceNow, and Palantir for enterprise automation scenarios. Oversee graph and vector-based storage layers (Neo4j, Pinecone, Milvus) and their alignment with Knowledge Graphs / Agent Context Memory. Manage multi-disciplinary engineering squads spanning AI, MLOps, DevSecOps, and Cloud Infra. Enforce AI SDLC, MLOps, and Responsible AI checkpoints in alignment with KPMG Global Risk & Legal. Establish performance dashboards tracking velocity, agent uptime, and hallucination-free accuracy across environments. Drive quarterly WOW Demo and Board Showcases with Foundry and Client Advisory leadership. Translate domain workflows (Audit, Tax, Advisory) into agentic pipelines for efficiency, insight, and compliance automation. Co-create AI-enabled service models for zero-touch audit, policy assurance, digital twins, and finance anomaly detection. Serve as AI Engineering liaison for client-side pilots, coordinating with Consulting, Risk, and CIO stakeholders. AI Frameworks : LangChain, CrewAI, AutoGen, Semantic Kernel, HuggingFace, PyTorch, TensorFlow Data Platforms : Azure Fabric, Databricks, Snowflake, Synapse, Palantir Foundry Model Management : MLflow, Kubeflow, Arize, OpenTelemetry, Prometheus Architecture : Microservices, container orchestration (Kubernetes, Ray), event-driven design Security : Zero-Trust, OAuth2, Confidential AI, Keysafe, SBOM governance DevOps Stack : GitHub Enterprise, Azure DevOps, Terraform, Helm, CI / CD pipelines Proven track record in leading 50+ member global AI engineering squads across cloud and hybrid infrastructures. Deep understanding of business, risk, and regulatory context of Big 4 Audit / Tax / Advisory engagements. Strong executive communication and board reporting skills; experience presenting AI transformation metrics to CXO-level audiences. Ability to balance innovation velocity with compliance assurance under regulated enterprise environments. Ph.D. / Master’s in Computer Science, AI / ML, or related discipline. 12+ years in AI Engineering, including 5+ years in leadership roles. Experience within professional services, consulting, or enterprise AI transformation.
The Director – AI Engineering will lead the design, development, and deployment of enterprise-grade AI solutions across Audit, Tax, and Advisory domains. The role focuses on scaling Agentic AI, Headless AI Agents, AI Marketplaces and Data Ocean - driven platforms for both internal transformation and client-facing products.
This leader will shape the engineering vision, drive cross-functional squads, and ensure that all AI solutions adhere to KPMG’s Trusted AI Governance, Zero-Trust frameworks, and multi-cloud operational standards.
Responsbilities :
1. AI Engineering & Architecture Leadership
- Lead full lifecycle AI engineering from prototype to MVP to production across KPMG Audit, Tax, and Advisory use cases.
- Architect scalable Agentic AI systems integrated with Foundry pipelines, Agent Factory orchestration, and KDO lakehouse connectivity.
- Define modular AI agent architecture (stateless / headless / memory-enabled) using LangChain, CrewAI, LlamaIndex, and Azure AI Studio.
- Drive model optimization, fine-tuning, and RLHF strategies for both proprietary and open-weight models (GPT, Claude, Llama, Falcon).
2. Platform Ownership – AI Foundry, Agent Factory
3. Data & Integration Leadership
4. Delivery & Governance
5. Client-Facing & Internal Transformation
Required Technical Competencies
Leadership & Behavioral Competencies
Educational & Professional Background
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Director Engineering • India
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