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INFOPRO LEARNING logo — INFOPRO LEARNING Senior AI Developer | Onsite - Noida, India | Open to India-based candidates only at INFOPRO LEARNING
INFOPRO LEARNING

Senior AI Developer | Onsite - Noida, India | Open to India-based candidates only

Job · Full-timeIn OfficeNoidaEarly career1 openingVerified open on 24 Sept 2026

About this role

INFOPRO LEARNING is hiring for Senior AI Developer | Onsite - Noida, India | Open to India-based candidates only in Noida. This opening was published by INFOPRO LEARNING on their official recruitee careers board on 1 September 2026 and was verified as still open on 23 September 2026. About INFOPRO…

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Skills you'll use

PythonNLPPandasNumPyAWSAzureGCPDockerKubernetesGitGoCommunication

What you'll do

  • Own the end-to-end architecture of agentic and RAG systems on Azure — retrieval pipelines, agent workflows, prompt systems, and the APIs that serve them — and set the technical direction other engineers build against.
  • Define and enforce evaluation standards for AI features across the team: what "good" looks like, how it's measured, and when something is genuinely ready to ship, not just working in a demo.
  • Develop and oversee skills inference and proficiency models that turn evidence into skill scores enterprise customers can trust, including how that trust is established and defended under scrutiny.
  • Set data engineering standards in Microsoft Fabric, including how customer data from HR, learning, and job systems is sourced, cleaned, and governed so downstream AI pipelines can rely on it.
  • Make production tradeoffs on latency, cost, and reliability, and own the MLOps loop: versioning, monitoring, and retraining, at a standard other engineers are expected to follow.
  • Deploy on Azure with clean APIs, containers, and CI/CD as a baseline, and make the architecture calls (build vs. buy, framework vs. custom orchestration) that less senior engineers shouldn't be making alone.
  • Mentor and review the work of other engineers on the team, raising the rigor of evaluation discipline, responsible AI practice, and production readiness across the board.
  • Work daily with product and engineering peers to shape what gets built, explain tradeoffs clearly to both technical and non-technical stakeholders, and document decisions that others will rely on.
  • Practice responsible AI as a first-class engineering discipline: fairness, transparency, and explainability are requirements you're accountable for defending, not just implementing.
  • What We're Looking For

Who can apply

  • Practice responsible AI as a first-class engineering discipline: fairness, transparency, and explainability are requirements you're accountable for defending, not just implementing.
  • A substantial engineering career — typically 6–8+ years in software, ML, or AI engineering — that demonstrates independent judgment and the ability to own ambiguous, high-stakes problems without close supervision.
  • Deep, hands-on, enterprise-grade experience architecting agentic systems: RAG, tool calling, multi-agent orchestration, and the vector search and retrieval infrastructure behind them, built and operated under real enterprise constraints (security, compliance, multi-tenant data, SLAs) — not personal or academic projects alone.
  • Strong Python and the modern AI stack: fluent with PyTorch or TensorFlow, Hugging Face, scikit-learn, Pandas, and NumPy, at a level where you're reviewing others' code, not just writing your own.
  • Direct experience with the Microsoft AI stack (Azure AI Foundry, Azure OpenAI, Microsoft Agent Framework, Microsoft Fabric) is a real advantage. Deep, verifiable experience with equivalent enterprise platforms (e.g., AWS Bedrock, GCP Vertex AI) plus a credible plan for closing the Microsoft-stack gap quickly is also acceptable.
  • An evaluation mindset you can install in a team, not just apply to your own work: you've built evaluation harnesses, defined metrics, and made the case — with data — for what should and shouldn't ship.
  • MLOps and deployment fluency: Docker, Kubernetes, CI/CD, and operating models on Azure at a standard you'd hold a team to.
  • Software engineering fundamentals strong enough to mentor from: Git, testing, API design, and the patience to debug problems in large, messy, real-world datasets.

About INFOPRO LEARNING

About INFOPRO LEARNING • Build a performance-ready workforce with Infopro Learning's workforce transformation solutions. Unlock human potential and thrive in the Human+AI era. • Extend your team with scalable, flexible design, content & media production. • Human+AI : Transforming Workflows…
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