Backend Engineer LLM & Data Engineering

Overview

Full Time

Part Time

Accepts corp to corp applications

Contract - W2

Contract - Independent

Skills

API

Backend Development

Scalability

Large Language Models (LLMs)

Workflow

Collaboration

Data Engineering

FOCUS

Python

LangChain

Vertex

Vector Databases

Prompt Engineering

RESTful

Cloud Computing

Amazon Web Services

Google Cloud Platform

Google Cloud

Microsoft Azure

Extract

Transform

Load

ELT

Machine Learning (ML)

Artificial Intelligence

Software Security

Strong Authentication

Authorization

DevOps

Docker

Kubernetes

GitHub

Jenkins

Job Details

Role Summary

We are looking for a Backend Engineer with strong experience in Python, LLM integration, and data engineering. The ideal candidate will have hands-on expertise in prompt engineering, fine-tuning LLMs, and working with LangChain and vector databases, while also ensuring robust API and backend development on modern cloud platforms.

Key Responsibilities

Design, develop, and maintain backend services and APIs with a strong focus on scalability and performance.
Implement LLM-based solutions, including prompt engineering and fine-tuning of large language models.
Build and optimize pipelines leveraging LangChain, vector databases, and LLM frameworks (OpenAI, Vertex AI, Hugging Face Transformers, etc.).
Develop and integrate REST APIs to support AI-driven applications and workflows.
Work on cloud platforms (AWS, Google Cloud Platform, or Azure) for deployment, scaling, and monitoring.
Collaborate with cross-functional teams to deliver end-to-end AI-powered solutions.

Required Skills & Experience

5+ years of professional experience in software/data engineering with a backend focus.
Strong Python programming expertise.
Hands-on experience with LangChain, LLMs (OpenAI, Vertex AI, Hugging Face, etc.), and vector databases.
Knowledge of prompt engineering and LLM fine-tuning techniques.
Strong understanding of REST API design and integration.
Experience with cloud environments (AWS, Google Cloud Platform, or Azure).

Good to Have

Experience with ETL/ELT pipelines and handling large datasets.
Strong knowledge of data preprocessing for ML/AI applications.
Familiarity with application security (authentication, authorization, vulnerability mitigation).
Exposure to DevOps tools (Docker, Kubernetes, GitHub Actions, Jenkins, etc.).
Experience with FastAPI for building high-performance APIs.

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