Senior ML & AI Engineer

Responsibilities

• Lead the design and engineering of enterprise AI/ML, NLP, Generative BI, GenAI and Agentic AI solutions for regulated banking environments.
• Build reusable frameworks for RAG, LLM applications, agent workflows, requirements discovery, code/test generation and advanced analytics.
• Define and implement feature engineering, model and agent evaluation, prompt testing, human-in-the-loop review and acceptance criteria.
• Operationalize ML models and AI agents using MLOps pipelines, MLflow, CI/CD, model registries, monitoring, observability and rollback controls.
• Integrate enterprise LLMs with governed data, semantic layers, metadata, vector databases, BI platforms, APIs and cloud AI services.
• Lead technical reviews, production-readiness assessments, performance optimization, responsible AI, security, governance and mentoring of AI/ML engineering teams.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science or a related technical discipline.
• 10+ years of experience in software engineering, analytics, AI/ML or data science, with strong technical leadership in enterprise AI/ML delivery.
• Strong hands-on expertise in Python, Spark, Scala/Java, TensorFlow, PyTorch, scikit-learn, MLflow and modern LLM/Agent frameworks.
• Proven experience with RAG, embeddings, vector search, LLMs, Agentic AI, prompt engineering, model evaluation, monitoring and drift detection.
• Strong knowledge of Hadoop/Cloudera, cloud AI services, Kubernetes, APIs, MLOps, CI/CD, observability, model governance and responsible AI.
• Banking domain experience across AML, risk, payments, finance or customer analytics, with strong communication, stakeholder management and mentoring skills; cloud ML/AI or Databricks certifications are preferred.