We are looking for a Principal Technical Consultant – Data Engineering & AI who can lead modern data and AI initiatives end-to-end — from enterprise data strategy to scalable AI/ML solutions and emerging Agentic AI systems. This role demands deep expertise in cloud-native data architectures, advanced machine learning, and AI solution delivery, while also staying at the frontier of technologies like LLMs, RAG pipelines, and AI agents. You’ll work with C-level clients to translate AI opportunities into engineered outcomes. ### Roles and Responsibilities * AI Solution Architecture & Delivery: * + Design and implement production-grade AI/ML systems, including predictive modeling, NLP, computer vision, and time-series forecasting. + Architect and operationalize end-to-end ML pipelines using MLflow, SageMaker, Vertex AI, or Azure ML — covering feature engineering, training, monitoring, and CI/CD. + Deliver retrieval-augmented generation (RAG) solutions combining LLMs with structured and unstructured data for high-context enterprise use cases. * Data Platform & Engineering Leadership: * Build scalable data platforms with modern lakehouse patterns using: * Ingestion: Kafka, Azure Event Hubs, Kinesis * Storage & Processing: Delta Lake, Iceberg, Snowflake, BigQuery, Spark, dbt * Workflow Orchestration: Airflow, Dagster, Prefect * Infrastructure: Terraform, Kubernetes, Docker, CI/CD pipelines * Implement observability and reliability features into data pipelines and ML systems. * Agentic AI & Autonomous Workflows (Emerging Focus): * Explore and implement LLM-powered agents using frameworks like LangChain, Semantic Kernel, AutoGen, or CrewAI. * Develop prototypes of task-oriented AI agents capable of planning, tool use, and inter-agent collaboration for domains such as operations, customer service, or analytics automation. * Integrate agents with enterprise tools, vector databases (e.g., Pinecone, Weaviate), and function-calling APIs to enable context-rich decision making. * Governance, Security, and Responsible AI:- Establish best practices in data governance, access controls, metadata management, and auditability. * Ensure compliance with security and regulatory requirements (GDPR, HIPAA, SOC2). * Champion Responsible AI principles including fairness, transparency, and safety. Consulting, Leadership & Practice Growth: * Lead large, cross-functional delivery teams (10–30+ FTEs) across data, ML, and platform domains. * Serve as a trusted advisor to clients’ senior stakeholders (CDOs, CTOs, Heads of AI). * Mentor internal teams and contribute to the development of accelerators, reusable components, and thought leadership. ### Key Skills * 12+ years of experience across data platforms, AI/ML systems, and enterprise solutioning * Cloud-native design experience on Azure, AWS, or GCP * Expert in Python, SQL, Spark, ML frameworks (scikit-learn, PyTorch, TensorFlow) * Deep understanding of MLOps, orchestration, and cloud AI tooling * Hands-on with LLMs, vector DBs, RAG pipelines, and foundational GenAI principles * Strong consulting acumen: client engagement, technical storytelling, stakeholder alignment ### Qualifications * Master’s or PhD in Computer Science, Data Science, or AI/ML * Certifications: Azure AI-102, AWS ML Specialty, GCP ML Engineer, or equivalent * Exposure to agentic architectures, LLM fine-tuning, or multi-agent collaboration frameworks * Experience with open-source contributions, conference talks, or whitepapers in AI/Data