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Principal AI Architect - MLOps/NLP

10 years

0 Lacs

Pune Maharashtra India

Posted:6 days ago| Platform: Linkedin logo

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Skills Required

ai leadership drive vision engineering coding design ml support model deployment learning data risk monitoring governance compliance regulations strategy training testing ethics development management xgboost tensorflow openai mlflow fastapi docker kubernetes airflow scoring forecasting trading aws sagemaker azure vertex databricks kafka aix fiddler portfolio spark sql nosql mongodb gcp programming python java scala software communication

Work Mode

On-site

Job Type

Full Time

Job Description

Employment Type : Full-Time.Relevant Experience : 10+ years

Key Responsibilities

  • AI-First Leadership : Define and drive DB Techs AI vision, re-architect systems into AI-native services,
integrate tools like Cursor/Relevance AI, and mentor teams in prompt engineering, Vibe Coding, and
autonomous testing.
  • Architect Scalable AI Systems : Design enterprise-scale AI/ML platforms that support real-time analytics,
model deployment, and continuous learning in financial products and services.
  • Lead Solution Design : Collaborate with data scientists, engineers, and business stakeholders to build and
integrate AI models into core platforms (e.g., risk engines, transaction monitoring, robo-advisors).
  • Ensure Governance & Compliance : Implement AI systems that meet financial regulations (e.g., GDPR,
PCI-DSS, FFIEC, Basel III) and uphold fairness, explainability, and accountability.
  • Drive MLOps Strategy : Establish and maintain robust pipelines for data ingestion, feature engineering,
model training, testing, deployment, and monitoring.
  • Team Leadership : Provide technical leadership to data science and engineering teams. Promote best
practices in AI ethics, version control, and reproducibility.
  • Identify areas where AI can deliver business value and lead the development of proofs-of-concept
(PoCs).
  • Evaluate the feasibility, cost, and impact of new AI initiatives.
  • Define best practices\standards for model lifecycle management (training, validation, deployment,
monitoring)- Evaluate Emerging Technologies : Stay ahead of developments in generative AI, LLMs, and FinTech-specific AI tools, and drive their strategic adoption.

Technical Skills And Tools

ML & AI Frameworks :

  • Scikit-learn, XGBoost, LightGBM, TensorFlow, PyTorch
  • Hugging Face Transformers, OpenAI APIs (for generative and NLP use cases)

MLOps & Deployment

  • MLflow, Kubeflow, Seldon Core, KServe, Weights & Biases
  • FastAPI, gRPC, Docker, Kubernetes, Airflow

FinTech-Specific Applications

  • Credit scoring models, Fraud detection algorithms
  • Time series forecasting, NLP for financial documents/chatbots
  • Algorithmic trading models, AML (Anti-Money Laundering) systems

Cloud & Data Platforms

  • AWS SageMaker, Azure ML, Google Vertex AI
  • Databricks, Snowflake, Kafka, BigQuery, Delta Lake

Monitoring & Explainability

  • SHAP, LIME, Alibi, Evidently AI, Arize AI
  • IBM AIX 360, Fiddler AI

Required Qualifications

  • Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or a related field;
PhD is a plus.
  • 10+ years of experience in AI/ML, including 35 years in architectural roles within FinTech or other highly
regulated industries.
  • Proven track record of building and deploying AI solutions in areas such as fraud detection, credit risk
modeling, or portfolio optimization.

Strong Hands-on Expertise In

  • Machine Learning : scikit-learn, XGBoost, LightGBM, TensorFlow, PyTorch
  • Data Engineering : Spark, Kafka, Airflow, SQL/NoSQL (MongoDB, Neo4j)
  • Cloud & MLOps : AWS, GCP, or Azure; Docker, Kubernetes, MLflow, SageMaker, Vertex AI
  • Programming : Python (primary); Java or Scala (optional)
  • Solid software engineering background with experience integrating ML models into scalable production
systems.
  • Excellent communication skills with the ability to influence both technical and non-technical stakeholders.
(ref:hirist.tech)

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