Gen AI

We are seeking a highly skilled Senior AI / GenAI Engineer to design, develop, and deploy enterprise-scale Generative AI solutions. The ideal candidate should possess strong hands-on experience in Advanced Retrieval-Augmented Generation (RAG) architectures, Agentic AI systems, LLM orchestration frameworks, and production-grade AI applications. The role requires expertise in translating business requirements into scalable AI solutions and driving end-to-end implementation from experimentation to production.

Knowledge of Snowflake and related cloud data platforms is desirable but not mandatory.

Mandatory Skills

Generative AI & LLMs

• Strong hands-on experience with Large Language Models (LLMs) and Generative AI application development.
• Experience with prompt engineering, prompt optimization, and evaluation frameworks.
• Expertise in LLM benchmarking, accuracy evaluation, hallucination assessment, and model performance monitoring.
• Experience working with OpenAI, Azure OpenAI, Anthropic, Llama, Mistral, or similar foundation models.

Advanced RAG (Mandatory)

• Extensive experience designing and implementing Advanced RAG architectures.

• Hands-on expertise in:

• Hybrid Search (Vector + Keyword Search)
• Semantic Search
• Metadata Filtering
• Parent-Child Retrieval
• Multi-Vector Retrieval
• Context Compression
• Re-ranking Techniques
• Query Expansion and Query Transformation
• Knowledge Graph-based Retrieval
• Adaptive / Agentic RAG
• Multi-hop Retrieval

• Citation and Grounded Response Generation

• Experience with vector databases such as Pinecone, Weaviate, Chroma, FAISS, Azure AI Search, or similar platforms.
• Experience evaluating retrieval quality using Precision@K, Recall@K, MRR, NDCG, and related metrics.

Machine Learning & NLP

• Strong understanding of Machine Learning and Natural Language Processing concepts.
• Experience in model development, feature engineering, model evaluation, and production deployment.
• Familiarity with classification, forecasting, prediction, and optimization use cases.

Programming & Development

• Strong proficiency in Python.
• Experience with REST APIs and microservice-based architectures.
• Experience working with SQL databases and data processing pipelines.
• Familiarity with Git, CI/CD, testing frameworks, and MLOps practices.

Preferred Skills

Snowflake (Optional)

• Experience with Snowflake architecture and data warehousing concepts.
• Exposure to Snowflake Cortex, AI functions, and cost optimization.
• Understanding of data processing pipelines, warehouse sizing, and performance tuning.

Cloud Platforms

• AWS(Preferred)
• GCP

Key Responsibilities

• Design and develop enterprise GenAI solutions leveraging advanced RAG techniques.
• Build scalable AI applications and AI agents for business use cases.
• Develop and optimize retrieval pipelines for accuracy, latency, and cost.
• Conduct prompt engineering, evaluation, and model performance testing.
• Collaborate with business stakeholders to understand requirements and translate them into AI solutions.
• Implement monitoring and governance controls for AI applications.
• Support production deployments and ongoing model improvements.
• Mentor junior engineers and contribute to AI best practices.

Educational Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or a related field.

Nice-to-Have Experience

• Text-to-SQL applications.
• Enterprise document intelligence solutions.
• AI governance and model risk management practices.
• LLM observability tools such as LangSmith, TruLens, Arize Phoenix, or similar.
• Knowledge of financial services, insurance, or enterprise operations domains.