AWS Cloud Engineer

Remote anywhere in India. Client : Dell/DXC/Toyota MergeIT AWS Cloud Engineer - Automotive Data Science, AI GenAI Ops Intro. At DXC, we believe the power of insight comes from an intelligent, end-to-end approach to Big Data, Data Science, AI, and GenAI. DXC delivers managed AI, GenAI, and ML solutions and platforms that help our customers accelerate innovation, improve operational agility, and power the next generation of automotive intelligence. This requirement is part of the Toyota North America Data Science Operations team. The role is focused on deploying, monitoring, governing, and maintaining Data Science, AI, and GenAI models in production environments. The engineer will ensure seamless integration of AI solutions into operational workflows and bridge the gap between Data Science, AI Engineering, and IT operations. The role works closely with data scientists, data engineers, DevOps teams, and platform teams to automate and streamline the full lifecycle of models and GenAI applications, from development and validation to deployment, monitoring, optimization, and governance. AWS Cloud Engineer for Automotive Data Science, AI GenAI - Expert (f/m/d) Location: Offshore (India) Contract type: Full-time / Part-time Travel: Not expected

Role and Responsibilities

• Design, develop, and implement deployment pipelines for Data Science, ML, AI, and GenAI solutions on AWS cloud.
• Build and maintain CI/CD and CT pipelines using GitHub Actions, Airflow, or similar orchestration tools.
• Support deployment and lifecycle management of ML models, LLM-based applications, prompt workflows, embeddings, vector search, and API-based AI services.
• Collaborate with data scientists, GenAI engineers, and data engineers to understand technical requirements, solution design, and deployment processes; document standards and operating procedures.
• Continuously monitor and maintain ML and GenAI pipelines in production, ensuring performance, reliability, latency, cost efficiency, and model quality.
• Implement observability for AI/GenAI workloads, including model drift, data quality, prompt quality, hallucination indicators, latency, throughput, and cost metrics.
• Optimize pipelines and runtime environments for scalability, security, automation, and cost-effectiveness.
• Troubleshoot and resolve issues related to deployments, integrations, production incidents, and model/service performance.
• Ensure compliance with security, privacy, responsible AI, and data governance standards across all deployment activities.
• Support experimentation and release processes for model versions, prompt versions, feature pipelines, and evaluation workflows.
• Keep up to date with emerging tools, best practices, and trends in AI Ops, MLOps, and LLMOps.
• Provide support, guidance, and knowledge sharing to other team members on deployment, automation, monitoring, and operational best practices.

Education and Competencies

• Bachelor s degree in computer science, engineering, informatics, data science, or equivalent qualification.
• Strong hands-on experience in Data Science, AI, and GenAI operations with AWS cloud platform services such as ECS, SageMaker, Batch, Lambda, API Gateway, S3, Redshift, CloudWatch, and related managed services.
• Experience with GenAI ecosystem components such as foundation models, prompt orchestration, retrieval-augmented generation, vector databases, model gateways, and evaluation/monitoring frameworks.
• Proficiency in Python and PySpark, with hands-on experience in containers, Airflow, GitHub Actions, SonarQube, and related automation/tooling stacks.
• Strong understanding of CI/CD, deployment automation, infrastructure as code, and production monitoring tools such as Datadog or equivalent observability platforms.
• Experience with MLOps, LLMOps, and AI lifecycle management in enterprise environments.
• Ability to understand architectural and technical dependencies in customer analytics and AI environments.
• Strong ability to translate business and technical requirements into scalable technical implementations.
• Confident communicator who can present effectively internally and with clients.
• Experience working in Agile delivery models.
• Strong team player who can coordinate effectively across distributed, global teams and time zones.

Disclaimer: This job posting and Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.