Artificial Intelligence Engineer

2 weeks ago

Gurgaon, Haryana, India Ambak Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Why This Role is Special

  • Greenfield + Impact:
    Build GenAI-powered financial solutions from scratch with minimal legacy baggage.
  • Enterprise-grade Scale:
    Your models will power risk, fraud, and personalization systems used in high-stakes fintech environments.
  • Innovation at Core:
    From RAG pipelines to fine-tuned LLMs, you'll explore and deploy the latest AI techniques.
  • End-to-End Ownership:
    From idea to production—data pipelines, modeling, compliance, and observability—you'll drive the full cycle.

Key Responsibilities:

  • AI/ML Development:
    Architect and implement advanced ML systems for fraud detection, credit scoring, personalization, and risk modeling.
  • Generative AI Solutions:
    Build and deploy LLM-powered tools for financial document summarization, chatbot automation, KYC workflows, and customer support.
  • LLM Experimentation:
    Work with OpenAI, Claude, LLaMA, Mistral, etc.—covering prompt engineering, fine-tuning, embeddings, and retrieval-augmented generation (RAG).
  • MLOps & Deployment:
    Own CI/CD for models, scalable serving, monitoring, and explainability (using MLflow, Kubeflow, or GCP/AWS/Azure ML stacks).
  • Cross-Functional Collaboration:
    Partner with product, compliance, and engineering teams to embed AI responsibly into fintech journeys.
  • Model Governance:
    Ensure fairness, bias mitigation, explainability (XAI), and adherence to financial regulatory standards.
  • Team Leadership:
    Mentor junior engineers and data scientists, fostering a high-performance AI culture.

Preferred Qualifications

  • Prior experience with fintech AI use-cases (fraud, risk, credit scoring, personalization).
  • Exposure to LangChain, Hugging Face, OpenAI APIs.
  • Experience with MLOps stacks (MLflow, SageMaker, Vertex AI, Kubeflow).
  • Contributions to AI research, open-source projects, or technical blogs/papers.

What Success Looks Like in 6 Months

  • Delivered at least 2 production-grade AI/GenAI systems impacting customer experience or financial operations.
  • Established scalable, compliant, and monitored ML pipelines.
  • Built a strong AI/ML engineering foundation for 's long-term roadmap.
  • Actively mentored team members and elevated AI culture across the org.

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