Senior Platform Engineer - Data & AI
- Equinix
- 8 - 12 years
- Bengaluru
- 1 month ago
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Job Description
We re looking for a Senior Platform Engineer with a strong foundation in data architecture, distributed systems, and modern cloud-native platforms to architect, build, and maintain intelligent infrastructure and systems that power our AI, GenAI and data-intensive workloads.
You ll work closely with cross-functional teams, including data scientists, ML & software engineers, and product managers & play a key role in designing a highly scalable platform to manage the lifecycle of data pipelines, APIs, real-time streaming, and agentic GenAI workflows, while enabling federated data architectures. The ideal candidate will have a strong background in building and maintaining scalable AI & Data Platform, optimizing workflows, and ensuring the reliability and performance of Data Platform systems.
Responsibilities
Platform & Cloud Engineering
- Develop and maintain real-time and batch data pipelines using tools like Airflow, dbt, Dataform, and Dataflow/Spark
- Design and develop event-driven architectures using Apache Kafka, Google Pub/Sub, or equivalent messaging systems
- Build and expose high-performance data APIs and microservices to support downstream applications, ML workflows, and GenAI agents
- Architect and manage multi-cloud and hybrid cloud platforms (e.g., GCP, AWS, Azure) optimized for AI, ML, and real-time data processing workloads
- Build reusable frameworks and infrastructure-as-code (IaC) using Terraform, Kubernetes, and CI/CD to drive self-service and automation
- Ensure platform scalability, resilience, and cost efficiency through modern practices like GitOps, observability, and chaos engineering
Data Architecture & Governance
- Lead initiatives in data modeling, semantic layer design, and data cataloging, ensuring data quality and discoverability across domains
- Implement enterprise-wide data governance practices, schema enforcement, and lineage tracking using tools like DataHub, Amundsen, or Collibra
- Guide adoption of data fabric and mesh principles for federated ownership, scalable architecture, and domain-driven data product development
AI & GenAI Platform Integration
- Integrate LLM APIs (OpenAI, Gemini, Claude, etc.) into platform workflows for intelligent automation and enhanced user experience
- Build and orchestrate multi-agent systems using frameworks like CrewAI, LangGraph, or AutoGen for use cases such as pipeline debugging, code generation, and MLOps
- Experience in developing and integrating GenAI applications using MCP and orchestration of LLM-powered workflows (e.g., summarization, document Q&A, chatbot assistants, and intelligent data exploration)
- Hands-on expertise building and optimizing vector search and RAG pipelines using tools like Weaviate, Pinecone, or FAISS to support embedding-based retrieval and real-time semantic search across structured and unstructured datasets
Engineering Enablement
- Create extensible CLIs, SDKs, and blueprints to simplify onboarding, accelerate development, and standardize best practices
- Streamline onboarding, documentation, and platform implementation & support using GenAI and conversational interfaces
- Collaborate across teams to enforce cost, reliability, and security standards within platform blueprints
- Act as a thought leader across engineering by introducing platform enhancements, observability, and cost optimization techniques
- Mentor junior engineers and foster a culture of ownership, continuous learning, and innovation
Qualifications
- 8-12 years of hands-on experience in Platform or Data Engineering, Cloud Architecture, AI Engineering roles
- Strong programming background in Java, Python, SQL, and one or more general-purpose languages
- Deep knowledge of data modeling, distributed systems, and API design in production environments
- Proficiency in designing and managing Kubernetes, serverless workloads, and streaming systems (Kafka, Pub/Sub, Flink, Spark)
- Experience with metadata management, data catalogs, data quality enforcement, and semantic modeling & automated integration with Data Platform
- Proven experience building scalable, efficient data pipelines for structured and unstructured data
- Experience with GenAI/LLM frameworks and tools for orchestration and workflow automation
- Experience with RAG pipelines, vector databases, and embedding-based search.
- Familiarity with observability tools (Prometheus, Grafana, OpenTelemetry) and strong debugging skills across the stack
- Experience with ML Platforms (MLFlow, Vertex AI, Kubeflow) and AI/ML observability tools
- Prior implementation of data mesh or data fabric in a large-scale enterprise
- Experience with Looker Modeler, LookML, or semantic modeling layers
Why You ll Love This Role
- Drive technical leadership across AI-native data platforms, automation systems, and self-service tools
- Collaborate across teams to shape the next generation of intelligent platforms in the enterprise
- Work with a high-energy, mission-driven team that embraces innovation, open-source, and experimentation
Job Classification
Industry: InternetFunctional Area / Department: Engineering - Software & QARole Category: DBA / Data warehousingRole: Database Architect / DesignerEmployement Type: Full timeContact Details:
Company: EquinixLocation(s): Bengaluru+ View Contact
Keyskills: metadata Data modeling Debugging Workflow Data quality Apache Open source Distribution system SQL Python
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