Senior AI Engineer

Nokia

Senior AI Engineer working on intelligent document processing and conversational AI systems at Nokia. Designing pipelines and deploying solutions on Databricks and Azure.

Posted 5/26/2026full-timeNoida • 🇮🇳 IndiaSeniorWebsite

Tech Stack

Tools & technologies

AzurePySparkPythonVault

About the role

Key responsibilities & impact

Intelligent Document Processing. Design and ship OCR + LLM pipelines that extract, classify, and validate information from scanned documents and PDFs. You'll own the full loop — from layout-aware parsing to entity extraction, confidence scoring, and feedback-driven improvement.
Conversational AI on enterprise data. Build copilot-style assistants and query interfaces over our Databricks data products, with proper authentication, role-based access, and grounded responses.
End-to-end delivery on Databricks and Azure. PySpark pipelines, Delta Lake, MLflow for experiment tracking and model registry, batch and real-time inference. Deploy on Azure with Azure OpenAI, Azure AI services, ADLS, Key Vault, and proper monitoring. Set up CI/CD and MLOps practices that make releases boring.
Reusable foundations. Prompt patterns, evaluation harnesses, pipeline components, model templates — the assets that let the team move faster on the next use case.

Requirements

What you’ll need

Strong Python and PySpark skills, with real experience shipping ML or data products to production
Solid foundation in classical ML (classification, clustering, similarity, anomaly detection) — you know when not to reach for an LLM
Hands-on experience with LLMs in production: RAG, extraction, evaluation, prompt design
Databricks delivery experience (Delta Lake, MLflow, performance tuning)
Comfortable on Azure: identity, secrets management, networking, and the AI/data services
Engineering discipline: Git, code review, testing, clear documentation
Fluent with AI coding assistants (Cursor, Claude Code, Copilot, or similar) as part of your daily workflow
Able to work directly with business stakeholders, debug across the stack, and explain trade-offs clearly.
Experience with OCR pipelines and document AI in production
Exposure to LLM evaluation frameworks and automated testing for AI systems
Experience with Responsible AI, security controls, and enterprise compliance

Benefits

Comp & perks

Health insurance
Flexible working hours
Professional development opportunities

ATS Keywords

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Hard Skills & Tools

PythonPySparkclassical MLOCRLLMsRAGDatabricksDelta LakeMLflowMLOps

Soft Skills

engineering disciplineclear documentationcommunicationstakeholder engagementdebuggingtrade-off explanation