AI Engineer Generative AI Platform Engineering | Remote |

AI Engineer – Generative AI Platform Engineering

CONTRACTUAL-REMOTE

Experience - 6+ Years

About the Role

We are looking for an experienced AI Engineer – Generative AI Platform Engineering to join our engineering team and help build scalable, secure, and enterprise-grade Generative AI capabilities.

This is a hands-on individual contributor role focused on developing reusable GenAI frameworks, platform services, APIs, agentic applications, RAG solutions, and AI/ML lifecycle capabilities. You will work closely with engineers, architects, data scientists, product owners, and business stakeholders to accelerate the adoption of Generative AI across enterprise applications.

The ideal candidate combines strong Python and software engineering expertise with practical experience in Generative AI, AI/ML platforms, APIs, cloud-native technologies, containers, and data engineering.

Key Responsibilities

• Design, develop, and enhance enterprise-grade Generative AI platform services, frameworks, APIs, and reusable components.
• Build AI-powered applications, AI agents, agentic workflows, RAG solutions, and MCP-enabled services.
• Develop scalable REST APIs and microservices using Python, FastAPI, or similar frameworks.
• Build capabilities supporting the AI/ML lifecycle, including model development, fine-tuning, deployment, inference, monitoring, and observability.
• Integrate LLMs, vector databases/stores, inference services, model-serving technologies, and AI orchestration frameworks.
• Develop event-driven and streaming applications using technologies such as Kafka and distributed processing platforms.
• Build and maintain CI/CD pipelines, automated testing, deployment automation, and DevOps workflows.
• Work with containerized and cloud-native environments using Docker, Kubernetes, and distributed computing platforms.
• Implement enterprise security mechanisms including API Gateway integration, JWT authentication, and secure API/service communication.
• Contribute to platform observability, performance optimization, resiliency, and operational excellence.
• Collaborate with architects, platform engineers, data scientists, product owners, and business teams on solution design and delivery.
• Participate in Agile ceremonies, technical design discussions, code reviews, estimation, and story refinement.
• Troubleshoot production issues and continuously improve the reliability, scalability, and performance of platform services.
• Evaluate emerging GenAI technologies and contribute innovative solutions to enhance enterprise AI capabilities.

Required Qualifications

• 6+ years of professional software engineering experience.
• Strong hands-on experience with Python and production-grade application development.
• Experience developing Generative AI, AI/ML, Data Science, Data Engineering, or analytics applications in enterprise environments.
• Strong understanding of Generative AI and AI/ML platform architectures.
• Hands-on experience with modern LLM/GenAI frameworks and tools.
• Experience developing scalable REST APIs and microservices using FastAPI or similar frameworks.
• Experience with RAG, vector stores/databases, LLM integration, inference services, or model-serving technologies.
• Experience with AI/ML lifecycle tools or frameworks such as MLflow, Kubeflow, or equivalent technologies.
• Strong understanding of software engineering fundamentals, including Git, CI/CD, automated testing, code reviews, and Agile development.
• Experience with containers and Kubernetes in cloud-native or distributed environments.
• Understanding of application security concepts including JWT, API gateways, authentication, and authorization.
• Strong problem-solving, communication, collaboration, and technical design skills.
• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related technical discipline.

Preferred Qualifications

• Hands-on experience building AI agents, MCP servers, or multi-agent orchestration solutions.
• Strong experience developing production-grade RAG applications.
• Knowledge of prompt engineering, model evaluation, LLM observability, and AI evaluation frameworks.
• Experience with Kafka, event-driven architectures, and streaming applications.
• Familiarity with metadata management, data lineage, data governance, semantic layers, and data quality.
• Experience with enterprise AI governance, responsible AI, security, and compliance practices.
• Exposure to large-scale Generative AI platforms and self-service developer ecosystems.
• Experience with cloud platforms and cloud-native AI/ML infrastructure.
• Technical Skills

Primary: Generative AI / GenAI Platforms

Secondary: Python, Machine Learning, Data Engineering

Additional: RAG, LLMs, AI Agents, MCP, FastAPI, REST APIs, Microservices, MLflow, Kubeflow, Vector Databases, Kafka, Docker, Kubernetes, CI/CD, Cloud Engineering, AI/ML Lifecycle, Model Serving, AI Observability