Forward Deployed Engineer Data Engineering & GenAI

Title: Forward Deployed Engineer – Data Engineering & GenAI
Location: San Jose, CA (Local Candidates Preferred)

• Local candidates preferred.

• Please share the candidate's availability for an interview next week with overlapping IST working hours .

Job Description

We are looking for a Forward Deployed Engineer – Data Engineering & GenAI with strong experience in data engineering, cloud platforms, and Large Language Models (LLMs). The ideal candidate will work closely with business stakeholders to design and implement scalable data and AI solutions while supporting production environments.

Required Qualifications

• 8+ years of experience in Data Engineering or Software Engineering , preferably working with large-scale financial or transactional data.

• Strong SQL skills with hands-on experience in BigQuery or an equivalent modern cloud data warehouse.

• Proficiency in Python and/or Java for data pipeline development and automation.

• Experience with Google Cloud Platform (GCP)services such as:

  • BigQuery

  • Cloud Composer (Airflow)

  • Dataflow

  • Pub/Sub

  • or equivalent cloud technologies.

• Hands-on experience building applications with Large Language Models (LLMs) , including:

  • Prompt Engineering

  • Function/Tool Calling

  • Retrieval-Augmented Generation (RAG) Pipelines

• Strong understanding of ETL/ELT architecture , data modeling, and large-scale performance optimization.

• Excellent communication skills with the ability to translate ambiguous business requirements into well-defined technical solutions.

• Experience collaborating directly with non-technical stakeholders, including Operations, Compliance, and Finance teams.

• Ability to thrive in fast-paced environments with shifting priorities and production support responsibilities.

Preferred Qualifications

• Experience developing solutions using Claude, OpenAI, or similar LLM APIs in production or internal applications.

• Familiarity with Model Context Protocol (MCP) , including building or configuring MCP servers/skills that connect LLMs with internal tools.

• Experience with Vector Databases and Embedding-based Search for RAG applications.

• Knowledge of Financial Reconciliation processes, including PDA, CASH, VDA, SDA matching, or equivalent reconciliation workflows.

• Experience with AI adoption analytics , usage monitoring, cost optimization, and cloud performance tuning at scale.