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.
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