AI/ML Presales Engineer

ResponsibilitiesEngage with clients to identify AI/ML use cases and translate business needs into technical solutions.Develop and present proposals, PoCs, and blueprints showcasing AI/ML integrated with modern data infrastructure.Design scalable data ingestion and model deployment strategies with a focus on performance and maintainability.Collaborate with sales, product, and engineering to ensure alignment between client needs and delivery capabilities.Guide clients through AI feasibility assessments, lifecycle planning, and readiness evaluations.Support integration of AI via cloud platforms, APIs, or on-prem inference engines.Stay current with AI/ML trends—including generative AI, foundation models, AutoML, and vector databases—and apply innovations to solution design.Document solution architectures, data flows, and ML lifecycle strategies for smooth handover to implementation teams.Champion best practices in MLOps, explainability, and responsible AI.RequirementsBachelor’s in Computer Science, Data Science, AI/ML, or related field (or equivalent experience/certifications).2–3 years in presales, solution architecture, or technical consulting, focused on AI/ML or data-driven solutions.Experience with AI/ML workflows, data pipelines, and model deployment.Proficient in AI/ML tools (e.g., TensorFlow, PyTorch, MLflow) and cloud platforms (SageMaker, Vertex AI, Azure ML).Solid understanding of data engineering, MLOps practices, and distributed systems (Kafka, Spark, Hadoop).Familiar with responsible AI, data governance, and regulatory compliance.Ability to present end-to-end AI solutions.Cloud or AI certifications are a plus.