Enterprise Architect

Job description

20+ years in IT, with at least 15+ years designing and delivering AI/ML solutions at enterprise scale.A proven record of leading multiple AI programs in parallel to production, with cross-functional teams, budgets and measurable business outcomes.Hands-on depth across classical ML, deep learning (NLP, computer vision, time series) and GenAI (LLMs, RAG, fine-tuning, agents).Production experience on at least one major cloud (AWS, Azure or GCP) and its AI/ML services.Experience in client-facing, consulting or solution-architect roles, including shaping large engagements and proposals.Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics or a related field. A Master's or PhD is preferred. Key Responsibilities Key responsibilities AI architecture and strategy: Define the enterprise AI reference architecture and roadmap across ML, deep learning, GenAI, RAG and agentic systems. Make build, buy or partner calls on models, platforms and vendors. Delivery ownership: Lead end-to-end delivery of multiple concurrent AI programs, from use-case discovery and proof of concept to production and scale. Own scope, timelines, quality and risk. Solution design and review: Architect scalable, secure and cost-efficient solutions. Review designs for data pipelines, model serving, latency and inference cost. MLOps and LLMOps: Set standards for model CI/CD, experiment tracking, feature stores, evaluation, monitoring, drift detection and rollback. Responsible AI and governance: Build security, privacy, fairness, explainability and regulatory compliance into every solution. Define guardrails for GenAI use. Stakeholder engagement: Work with CXOs, business owners and clients to turn business problems into AI solutions with measurable ROI. Support solution shaping, pre-sales and executive presentations. Team leadership: Lead and mentor data scientists, ML engineers and solution architects. Run the architecture review board and hire for the team. Innovation and reuse: Track new research and tools, run proofs of concept, and build reusable accelerators and IP. Skill Requirements . ML and Deep Learning Scikit-learn XGBoost PyTorch TensorFlow Natural Language Processing (NLP) Computer Vision Forecasting Recommender Systems 2. GenAI and Agents LLM APIs GPT Claude Llama Mistral Prompt Engineering Fine-tuning LoRA / PEFT Retrieval-Augmented Generation (RAG) Vector Databases LangChain LlamaIndex LangGraph LLM Evaluation Guardrails 3. MLOps and LLMOps MLflow Kubeflow Amazon SageMaker Azure ML Vertex AI Databricks Model Registry CI/CD Model Monitoring Drift Detection 4. Data Platforms Apache Spark Apache Kafka Databricks Snowflake Lakehouse Platforms Feature Stores Data Governance 5. Cloud and Infrastructure AWS Microsoft Azure Google Cloud Platform (GCP) Kubernetes Docker Terraform GPU Optimization vLLM NVIDIA Triton Inference Serving 6. Security and Compliance Identity and Access Management (IAM) Data Privacy Model Risk Management Responsible AI GDPR EU AI Act 7. Programming Languages Primary: Python – Expert SQL Good to have: Java Scala Go Other Requirements Apply now Information at a Glance Why HCLTech? At HCLTech, you'll supercharge your potential. You'll find your career. And you'll find your spark. All at a place that knows that helping its customers stay on top starts by putting its people first. HCLTech is a global technology company, home to more than 230,000 people across 60 countries, delivering industry-leading capabilities centered around digital, engineering, cloud and AI, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services. 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