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Hiring: AI Engineer – GenAI Platform Engineering
Experience: 10+ Years
Primary Skill: Generative AI / GenAI Platforms
Secondary Skills: Python | Machine Learning | Data Engineering
Tertiary Skill: Hadoop
Role: Senior AI / Platform Engineering
🔹 Role Overview
We are looking for a highly experienced AI Engineer – GenAI Platform Engineering to design and build enterprise-scale Generative AI, AI/ML, Data Engineering, and Data Platform capabilities.
The role will focus on developing scalable, secure, and reusable AI platform services supporting LLM applications, RAG, agentic AI, data science, event-driven architectures, and AI/ML lifecycle automation.
🔹 Key Responsibilities
Lead architecture and engineering for enterprise GenAI, AI/ML, Data Engineering, Metadata, Data Quality, and Event Streaming platforms.
Design reusable, self-service platform services covering data ingestion, experimentation, model development, deployment, monitoring, and governance.
Build LLM-powered applications, RAG solutions, agentic AI workflows, and MCP-enabled services.
Design event-driven and distributed architectures using technologies such as Kafka, Spark, and Flink.
Drive platform modernization using Kubernetes, Docker/containers, serverless, and cloud-native technologies.
Develop enterprise-grade APIs, microservices, and distributed systems for high-volume AI and data workloads.
Implement CI/CD, Infrastructure as Code, automation, and DevSecOps practices.
Ensure platforms meet enterprise standards for security, governance, scalability, reliability, compliance, and observability.
Conduct architecture and code reviews and provide technical mentorship to engineering teams.
Collaborate with architects, product owners, data scientists, engineers, and business stakeholders to deliver scalable AI solutions.
🔹 Must-Have Skills
10+ years of experience in AI, Data Science, Data Engineering, Analytics, or Platform Engineering.
Strong hands-on experience designing enterprise GenAI platforms.
Experience with LLMs, RAG, Agentic AI, prompt orchestration, vector databases, and AI governance.
Strong Python and AI/ML development experience.
Strong understanding of Data Engineering and distributed systems.
Experience with Kafka, Spark, Flink, or equivalent technologies.
Hands-on experience with Kubernetes, Docker/containers, and cloud-native platforms.
Experience building APIs, microservices, and scalable distributed applications.
Experience with CI/CD, DevSecOps, Infrastructure Automation, and observability.
Strong understanding of data governance, metadata, data lineage, data quality, security, and compliance.
🔹 Good to Have
MCP Servers
AI Gateways & Model Management
Prompt Management
Vector Databases
Knowledge Graphs
Enterprise AI Copilots
AI Workflow Orchestration
Responsible AI / AI Governance
Hadoop
Multi-cloud / Hybrid Cloud environments
Work arrangement
Yes
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