Full Stack Developer - AI/ML

ITC, Inc.
Fairfax, United States of America
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Intermediate

Job location

Remote
Fairfax, United States of America

Tech stack

Java
JavaScript
API
Artificial Intelligence
Airflow
Amazon Web Services (AWS)
Software Applications
Computer Vision
Azure
Big Data
Cloud Engineering
Computer Programming
Computer Literacy
Continuous Integration
ETL
Data Systems
DevOps
Design of User Interfaces
Python
Machine Learning
Natural Language Processing
TensorFlow
Software Deployment
TypeScript
Unstructured Data
Google Cloud Platform
Cloud Platform System
Azure
PyTorch
React
Large Language Models
Snowflake
Generative AI
Backend
Vue.js
Angular
Kubernetes
Information Technology
HuggingFace
Front End Software Development
Virtual Agents
REST
Data Pipelines
Docker
Databricks
Microservices

Job description

ITC Federal is seeking a highly skilled Full Stack Developer - AI/ML Engineer with a strong background in data engineering and full-stack development to support the design, development, and deployment of advanced AI-driven solutions. This role requires a unique blend of technical expertise and the ability to translate complex concepts into clear, customer-facing deliverables, including documentation, proposals, and solution artifacts.

The ideal candidate will have experience taking ideas from concept to production-building intelligent, scalable solutions and integrating them into enterprise environments to drive meaningful business outcomes. This position works closely with cross-functional teams to deliver innovative, production-ready capabilities leveraging modern cloud and AI technologies., * Design, develop, and deploy AI/ML solutions, including LLMs, NLP, computer vision, and predictive analytics

  • Build and implement Retrieval-Augmented Generation (RAG) pipelines and AI-powered applications
  • Integrate AI solutions into existing enterprise systems and workflows
  • Design and implement scalable data pipelines for ingestion, transformation, and processing of structured and unstructured data
  • Develop and maintain data lakehouse architectures
  • Build ETL/ELT workflows using tools such as Azure Data Factory, Apache Airflow, or similar
  • Develop end-to-end applications, including frontend, backend, and APIs
  • Create intuitive user interfaces for AI-driven applications
  • Deploy applications using cloud-native architectures (AWS, Azure, GCP)
  • Translate business requirements into technical architectures and working solutions
  • Integrate AI and data solutions into enterprise and cloud environments
  • Collaborate with cross-functional teams to deliver production-ready solutions
  • Clearly articulate complex technical concepts through written documentation, proposals, and solution artifacts

Requirements

  • Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or related field
  • 4+ years of experience in AI/ML, data engineering, or full-stack development
  • Strong programming skills in Python, JavaScript/TypeScript, or Java
  • Experience with AI/ML frameworks (TensorFlow, PyTorch, Hugging Face, OpenAI APIs)
  • Experience building data pipelines and working with big data technologies
  • Hands-on experience with cloud platforms (AWS, Azure, or GCP)
  • Experience with REST APIs, microservices, and frontend frameworks (React, Angular, or Vue)
  • Experience with LLMs, RAG architectures, and generative AI applications
  • Familiarity with Databricks, Snowflake, or lakehouse architectures
  • Experience with DevOps tools (Docker, Kubernetes, CI/CD pipelines)

PREFERRED QUALIFICATIONS:

  • Experience supporting federal government or GovCon environments
  • Experience contributing to proposals, technical responses, or solutioning efforts (e.g., white papers, RFP responses, technical volumes), This is a hybrid position requiring 3 days onsite and 2 days remote work per week. Candidates must be able to function in both office and remote environments, including extended periods of computer use and collaboration across distributed teams.

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