AI Engineer – GenAI Platform Engineering

Experience: 10+ Years

Location: Chennai / Pune

Work Mode: Hybrid – 3 Days WFO

Payroll: Haparz

Budget: Up to 30 LPA

Notice Period: Immediate / Short Notice preferred

Role Overview

We are looking for a senior AI Engineer / GenAI Platform Engineer to lead the design and engineering of enterprise-scale Generative AI and data platform capabilities.

The role involves building reusable, secure, scalable and governed platforms that enable self-service AI, data science, intelligent workflows and enterprise analytics. The ideal candidate should have strong hands-on experience across GenAI, Python, AI/ML platforms, data engineering, distributed systems, cloud-native technologies and platform engineering.

This is a platform engineering and architecture-heavy role, rather than a conventional ML model-development position.

Key Responsibilities

- Provide technical leadership for enterprise GenAI, AI/ML, Data Engineering, Data Quality, Metadata and Event Streaming platforms.
- Design reusable platform services supporting the complete AI lifecycle from data onboarding and preparation through experimentation, model deployment, inference, monitoring and governance.
- Architect and build Generative AI and agentic AI solutions, including LLM integrations, RAG pipelines, prompt orchestration, AI agents and MCP-enabled services.
- Design scalable event-driven and distributed architectures for high-volume AI and data workloads.
- Develop enterprise-grade APIs, microservices and platform services using Python and modern cloud-native technologies.
- Build self-service capabilities that allow engineering and data science teams to consume AI and data platform services efficiently.




- Define reference architectures, engineering standards, reusable frameworks and best practices for enterprise AI platforms.
- Work with Kubernetes, containers, serverless technologies and distributed computing frameworks for platform modernization.
- Design and implement metadata-driven platforms, data lineage, semantic layers, data quality and governance capabilities.
- Establish CI/CD, Infrastructure-as-Code, automated testing and DevSecOps practices.
- Implement observability, monitoring, security, resiliency, availability and disaster-recovery capabilities for critical AI platforms.
- Evaluate emerging GenAI, open-source and cloud technologies and build prototypes/POCs where appropriate.
- Conduct architecture and code reviews and provide technical mentorship to engineering teams.
- Collaborate with architects, product owners, data scientists, developers and business stakeholders.
- Drive modernization of legacy data science, analytics and AI ecosystems into scalable platform-based solutions.
- Communicate technical architecture and design decisions effectively with senior technical and business stakeholders.

Required Experience
- 10+ years of software/platform engineering experience with significant experience in AI, GenAI, Data Engineering or distributed systems.




- Strong hands-on experience building enterprise-scale Generative AI platforms or applications.
- Robust Python development experience.
- Experience with LLM integration, prompt engineering/orchestration, RAG, vector databases and AI/agent frameworks.
- Experience designing agentic AI architectures, intelligent workflows or MCP-based services.
- Strong understanding of AI/ML lifecycle platforms, model serving, evaluation, monitoring and observability.
- Strong experience with data engineering and distributed processing.
- Experience with technologies such as Kafka, Spark, Flink or equivalent.
- Experience with Kubernetes, Docker/containers and cloud-native architectures.
- Strong API, microservices and distributed-system development experience.
- Experience implementing CI/CD, Infrastructure-as-Code, automation and DevSecOps.
- Understanding of metadata management, data lineage, data quality and data governance.
- Strong understanding of security, scalability, resiliency, availability and operational excellence.

Preferred Experience
- Enterprise AI Gateway / LLM Gateway implementations.
- Model management and prompt-management platforms.
- Vector databases and enterprise knowledge platforms.
- Advanced RAG and agentic AI architectures.
- MCP servers and AI workflow orchestration.
- AI governance, responsible AI, compliance and risk controls.
- Internal AI copilots and self-service AI platforms.
- Cloud-native AI platforms across AWS, Azure, GCP or private cloud.
- Developer platforms and internal platform-as-a-product initiatives.
- Legacy analytics/data-science platform modernization.
- Hadoop ecosystem experience.

Work Location: Hybrid remote in Pune, Maharashtra

📌 Hiring AI Engineer – GenAI Platform Engineering (Pune)
🏢 Haparz
📍 Pune