Senior Lead Python AI/ML Engineer

Role Overview We are seeking an experienced and visionary Senior Lead Python AI/ML Engineer with Generative AI Capabilities to lead the design, development, and deployment of next-generation artificial intelligence and machine learning solutions based out of our Chennai center (operating in a Hybrid work model). With 10 to 12 years of hands-on software and machine learning engineering experience , the ideal candidate will drive the convergence of traditional predictive ML models and modern Foundation Model / GenAI architectures. In this role, you will be instrumental in building high-scale, low-latency AI solutions applied to Fraud Mitigation, Risk Scoring, and Loss Prevention across US Retail Banking products 2. Key Responsibilities AI/ML & Generative AI Architecture - Architect, build, and deploy production-grade Generative AI systems, including Retrieval-Augmented Generation (RAG) , autonomous agents, semantic search pipelines, and multi-modal AI workflows. - Integrate state-of-the-art Large Language Models (LLMs)—including Google Gemini , Anthropic Claude , and open-source models (Llama, Mistral)—optimizing for latency, cost, and accuracy. - Build domain-specific prompt engineering frameworks, fine-tuning pipelines (LoRA/QLoRA), model evaluation benchmarks, and guardrails to minimize hallucinations and bias. - Lead the architecture of predictive ML algorithms (anomaly detection, graph neural networks, supervised/unsupervised classifiers) tailored to real-time risk assessment. Software Engineering & System Scalability - Design resilient, low-latency, and horizontally scalable microservices and APIs in Python (FastAPI, Flask, AsyncIO) handling high-throughput transactional traffic. - Integrate vector databases (e.g., Pinecone, Milvus, Qdrant, Chroma, pgvector) with distributed caching and event streaming platforms (Kafka, RabbitMQ). - Implement robust MLOps and LLMOps practices (CI/CD pipelines, automated model retraining, observability with MLflow/Weights & Biases, model drift monitoring). Fraud Analytics & Domain Innovation - Collaborate closely with US-based and global Risk, Compliance, and Loss Prevention teams to build AI solutions targeting identity theft, account takeover (ATO), synthetic identity fraud, card-not-present (CNP) fraud, and transaction anomaly detection. - Utilize unstructured data (investigator notes, SAR filings, customer interaction logs) via GenAI to automate fraud triage and investigative summarization. - Ensure strict adherence to US Banking regulatory standards (FCRA, GLBA, Model Risk Management SR 11-7, Fair Lending, Explainable AI / XAI). Technical Leadership & Mentorship - Mentor senior/mid-level data scientists and software engineers across the Chennai engineering hub in modern GenAI patterns, clean code principles, and production readiness. - Drive technical roadmap, evaluate emerging AI frameworks, conduct proof-of-concepts (PoCs), and present architectural proposals to global engineering leadership. 3. Required Qualifications & Experience - Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Applied Mathematics, or a related quantitative field. - Total Experience: 10 to 12 years of professional experience in software engineering and production AI/ML system development. - Core Python Expertise: Advanced proficiency in Python 3.x (multiprocessing/asyncio, design patterns, profiling, packaging, and clean code paradigms). - Core ML Frameworks: Deep practical experience with PyTorch, TensorFlow, Scikit-learn, XGBoost, and LightGBM. - Generative AI Proficiency: - Demonstrated success building production GenAI applications (LangChain, LlamaIndex, CrewAI, AutoGen). - Hands-on experience with embedding models, dense retrieval, rerankers, and vector indexing strategies. - Distributed Systems & Cloud: Strong hands-on experience with cloud platforms (AWS, GCP, or Azure), containerization (Docker, Kubernetes), and distributed data processing (PySpark, Ray). - MLOps / LLMOps: Proven track record in orchestrating end-to-end ML lifecycles from data validation to real-time inference monitoring. 4. Preferred & Good-to-Have Skills - Google Gemini & Anthropic Claude: Hands-on experience with API integration, function calling/tools, context caching, and prompt optimization specifically for Google Gemini (Pro/Flash) and Anthropic Claude (Opus/Sonnet/Haiku). - Domain Knowledge (Fraud & Loss Prevention): - Experience designing fraud rule engines, anomaly detection platforms, or predictive risk models. - Familiarity with transaction monitoring, biometric behavioral analytics, and fraud consortium datasets. 5. Technical Skills Matrix Category Technologies & Tools Programming Languages Python (Advanced), SQL, Bash Generative AI & LLMs Anthropic Claude, Google Gemini, OpenAI GPT, Open-source LLMs (Llama, Mistral), LangChain, LlamaIndex, DSPy Classical & Deep ML PyTorch, TensorFlow, Scikit-Learn, XGBoost, LightGBM, Hugging Face Transformers Vector DBs & Search Pinecone, Milvus, Qdrant, Weaviate, FAISS, pgvector, Elasticsearch Backend & APIs FastAPI, Flask, AsyncIO, gRPC, REST Data & Streaming Apache Kafka, Apache Spark / PySpark, Pandas, Polars, DuckDB MLOps & DevOps MLflow, Kubeflow, Docker, Kubernetes, GitHub Actions, Terraform, Prometheus/Grafana Domain Tools & Standards Model Risk Management (SR 11-7), Explainable AI (SHAP, LIME), PII Masking 6. Key Performance Indicators (KPIs) - Model Performance & Accuracy: Precision/Recall trade-offs in fraud detection, false positive reduction, and sub-100ms real-time inference latency. - Engineering Excellence: Code quality, test coverage (>85%), modular design, and robust error handling. - Business Impact: Measurable reduction in fraud loss basis points and acceleration of investigator workflow efficiency through GenAI summarization/triage. - Mentorship & Global Delivery: On-time milestone delivery, technical capability elevation across local and global engineering pods. ------------------------------------------------------ Job Family Group: Technology ------------------------------------------------------ Job Family: Applications Development ------------------------------------------------------ Time Type: Full time ------------------------------------------------------ Most Relevant Skills Please see the requirements listed above. ------------------------------------------------------ Other Relevant Skills For complementary skills, please see above and/or contact the recruiter. ------------------------------------------------------ Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law. 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