Generative AI Engineer, Data & Analytics

The role aims to instill a culture of data aggregation, advanced analytics, and AI-driven insights across the organization. The incumbent will identify patterns in data to improve consumer experience, enhance decision-making, and contribute towards achieving organizational goals and objectives.

Key Responsibilities

Functional

• Scale analytics capability across business functions and guide the organizations data strategy.
• Organize, process, and analyze large, diverse datasets across multiple platforms.
• Identify and communicate key insights to influence product and business strategy.
• Collaborate with vendors and partners in a technical capacity on scope, approach, and deliverables.
• Develop proofs of concept to validate ideas and solutions.
• Partner with business teams to formalize analytical requirements and design robust, efficient, and reliable reporting solutions.
• Design and implement advanced statistical testing and models for problem solving.
• Deliver clear and concise insights to senior leadership, elevating analytics into strategic recommendations.
  

AI/ML & LLM-Specific

• Build, train, and fine-tune data pipelines for ML and LLM use cases (dataset creation, cleaning, augmentation, labeling workflows).
• Apply expertise in ML algorithms (e.g., XGBoost, SVM) and statistical modeling techniques (regression, segmentation, forecasting, hypothesis testing, A/B testing, decision trees, etc.).
• Work hands-on with modern LLMs and embeddings (OpenAI, Anthropic, LLaMA-family, Mistral, etc.).
• Implement instruction tuning/fine-tuning methods (LoRA, PEFT, adapters).
• Integrate AI models with backend and frontend systems using APIs, batching, caching, and streaming responses.
• Develop safe, secure, and compliant AI applications, including safety layers (prompt injection defense, hallucination reduction, PII redaction).
• Build and deploy scalable AI/ML systems using MLOps practices (Docker, Kubernetes, CI/CD).
• Work with frameworks and tools such as LangChain, Hugging Face Transformers, Ray/Serve, and vector databases (FAISS, Pinecone, Milvus).
  

Job Requirements

Qualifications

• M.Tech / B.E. / B.Tech / M.Sc. in Computer Science, Statistics, Mathematics, Operational Research, Econometrics, or a related quantitative field.
  

Experience

• Minimum 2+ years of experience in the analytics / AI / ML domain.
  
• Prior exposure to BFSI/NBFC industry is desirable.
  

Functional Competencies

• Strong analytical, logical reasoning, problem solving, and numerical aptitude
• Proven experience with large datasets and big data technologies (SQL, Hadoop, Hive).
• Advanced knowledge of data mining, statistical analysis, and ML algorithms.
• Hands-on expertise with Python for analytics and AI development.
• Proficiency in CI/CD, MLOps, and modern AI/ML engineering practices.
• Familiarity with Azure OpenAI, LangChain, Hugging Face, and related ecosystems.
• Knowledge of speech-to-text systems (e.g., Whisper, Indian languages a plus).
  

Desirable Skills

• Experience in BFSI/NBFC domain.
• Exposure to speech-to-text and multilingual NLP solutions.