AI & Data Engineer

About the role:

We are looking for a hybrid AI and Data Engineer to build the next generation of 'Agentic' systems. You will bridge the gap between raw structured/unstructured data and actionable AI, moving beyond simple chatbots to create autonomous agents that can reason, search, and execute complex workflows.

Role & responsibilities

Technical Qualifications:

1. GenAI & Agentic Development

• LLM Orchestration: 2+ years building and deploying AI-driven applications. You should be an expert in RAG pipelines and AI Agents using frameworks like LangChain, LlamaIndex, etc.
• Model Proficiency: Solid understanding of Transformer architectures (Gemini, GPT, Claude).
• Experience with fine-tuning, advanced prompt engineering, and optimizing context windows.
• Vector Expertise: Proven ability to build semantic search layers using PG Vector, embedding models, and Google Indexing.

2. Data Engineering & Scale

• Big Data Stack: Experience processing large-scale datasets using Python (Pandas/PySpark) or Scala.
• Warehousing & SQL: Professional experience with Snowflake or Redshift, including the ability to write high-performance Advanced SQL.
• Data Modeling: Ability to design dimensional data models optimized for low-latency AI consumption and high data quality.

3. Software Craftsmanship

• Production Standards: Focus on writing clean, maintainable code with robust CI/CD practices and ML Observability.

Preferred candidate profile

• 5+ years of experience in relevant technology
• Education: B.Tech/M.Tech in Computer Science or a related field.
• Advanced Agents: Experience experimenting with multi-agent systems for complex reasoning tasks.
• Cloud Infrastructure: Hands-on experience with AWS (Bedrock, Lambda) for deploying and scaling AI workloads.
• Gemini Ecosystem: Direct experience leveraging Google Gemini for multimodal or long-context applications