Data Engineer - AWS AI

Role Overview

This role is ideal for individuals who are passionate about applying their expertise in AI Engineering, Data Engineering, programming, data analysis, and problem-solving to real-world challenges. As a key member of our engineering team, you will support clients on their AI journey by developing solutions that drive measurable business value. This position plays a critical role in advancing Infocepts' strategic goals by delivering data-driven insights and enabling transformative AI/ML programs.

Responsibilities

• Design and maintain high-performance ETL/ELT pipelines on AWS using PySpark, Python, and SQL across EMR, Glue, Lambda, Step Functions, Redshift, and S3.
• Develop, fine-tune, and deploy LLMs (GPT-4 class, BERT, T5) for enterprise applications.
• Implement RAG using FAISS, Elasticsearch, LangChain, or LlamaIndex for grounding, vector search, and knowledge retrieval.
• Work with emerging enterprise AI platforms including Snowflake Cortex and Databricks Lakehouse AI.
• Contribute to solution architecture, AI governance, data security, and model lifecycle frameworks.

Requirements

• 3+ years of experience across AI/ML and Data Engineering.
• Bachelors degree in computer science engineering, or related field.
• Expert-level skills in Python, PySpark, Scala and advanced SQL.
• Hands-on experience with AWS (EMR) services.
• Working experience with LLMs, RAG, vector databases, and transformer-based architectures.
• Solid understanding of distributed systems, data modeling, and data platform design.

Skills

• Python
• PySpark
• AWS
• SQL
• LLM

Nice to Have

• Experience with Snowflake Cortex for secure enterprise LLM workloads.
• Experience with Databricks Genie / Lakehouse AI, Unity Catalog, Delta Live Tables.
• Knowledge of prompt engineering, safety guardrails, and agent tooling.
• Familiarity with feature stores, model registries, MLflow, or similar tooling.
• Knowledge of statistical methods, deep learning, and NLP techniques.