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Lead and grow the Data team, design cloud ML architectures, build production ML/AI solutions, guide data scientists to productionize models, run trainings and client workshops, and represent Sia externally.

Work as a Data Engineer consultant building cloud-native data platforms and ML infrastructure. Responsibilities include cloud architecture (GCP/AWS/Azure), containerization (Docker, Kubernetes), Python development, CI/CD, ETL/data pipelines, IaC, security implementation, and supporting deployment of Data Science and ML solutions for clients.

Maintain and optimize production ML algorithms and services: triage/fix bugs, profile and improve performance, implement parallelism, build and maintain REST APIs (Django/DRF or FastAPI), test/benchmark scalability and efficiency, ensure code quality (tests, type hints, CI/CD), and collaborate with product/data/QA to meet SLAs.

Lead design and delivery of scalable data architectures and pipelines across cloud platforms. Build data models, implement batch/streaming integrations, apply CI/CD and DataOps, mentor consultants, drive business development, and represent the firm in thought leadership and client engagements.

Lead client engagements delivering advanced predictive models and Generative AI/LLM solutions. Manage stakeholders and multidisciplinary teams, mentor colleagues, contribute to business development, and represent the firm in thought leadership and internal capability building.

Develop and optimize React-based user interfaces for AI-powered SaaS, improve client-side performance, ensure cross-browser compatibility, collaborate with backend and design teams, maintain code quality via tests and reviews, manage cloud deployments and IaC (Terraform, Helm), and support CI/CD pipelines.

Design, build, and deploy Generative AI solutions (RAG, agents, fine-tuning) using LLMs and vector DBs. Lead prototyping, model benchmarking, MLOps, cloud deployments, performance/ security/compliance, and cross-functional rollouts for enterprise PoCs and production systems.

Collaborate in multidisciplinary teams to develop statistical models, optimization solutions, and machine learning applications. Apply Generative AI and LLMs, extract actionable insights, present results, and support client workshops to solve business problems.

Lead design and delivery of scalable data architectures and pipelines on cloud platforms. Implement batch and streaming integration, data modeling across relational and NoSQL stores, and DataOps/CI-CD practices. Manage client engagements, mentor junior consultants, contribute to thought leadership, and drive business development for data engineering offerings.

Serve as a senior data engineering consultant: represent Sia in thought leadership, drive business development, manage client engagements, mentor junior consultants, and advise middle/senior management on data and AI initiatives across sectors like Energy and Finance.