Full Stack Engineer Enterprise AI Applications

Virginia, VA - USA

Monthly Salary: Not Disclosed

Posted on: 30+ days ago

Vacancies: 1 Vacancy

The job posting is outdated and position may be filled

Job Summary

Overview

Were seeking an exceptional Full Stack Engineer to build and scale our enterprise AI applications. Youll design and implement complete AI-powered features from database to UI working with cutting-edge LLM technology RAG systems and production ML infrastructure. This role combines full-stack development expertise with hands-on AI/ML engineering deploying intelligent systems that deliver real business value at scale.

Youll be a key technical contributor shipping production-ready AI features that users love while ensuring reliability performance and cost-effectiveness. This is an opportunity to work at the intersection of software engineering and artificial intelligence solving complex problems with modern technology.

What Youll Build

AI-Powered Applications

Design and implement end-to-end RAG (Retrieval-Augmented Generation) pipelines that enable intelligent document search and question-answering across enterprise knowledge bases
Build production-ready integrations with leading LLMs (GPT-4 Claude Gemini) that provide accurate contextual responses to user queries
Develop sophisticated prompt engineering strategies and evaluation frameworks to ensure consistent high-quality AI outputs
Create agent systems with tool integration capabilities that can autonomously complete complex tasks
Implement vector search solutions using Pinecone Weaviate or similar technologies for semantic similarity and knowledge retrieval

Full-Stack Features

Build scalable backend services using Python/FastAPI with type-safe APIs authentication and robust error handling
Develop responsive performant frontend applications using React/ with real-time streaming for LLM responses
Design and optimize database schemas spanning PostgreSQL MongoDB and Redis to support high-throughput AI workloads
Implement WebSocket servers and event-driven architectures for real-time user experiences
Create comprehensive testing strategies covering unit integration and end-to-end tests

Production Infrastructure

Deploy and manage ML/AI services using Docker containers and Kubernetes orchestration
Build and maintain CI/CD pipelines that enable rapid safe deployment of AI features
Implement infrastructure as code using Terraform to manage cloud resources (AWS Azure or GCP)
Set up comprehensive monitoring and observability using Datadog Prometheus/Grafana and LLM-specific tools (LangSmith Weights & Biases)
Optimize costs through intelligent caching batching strategies and model selection algorithms
Ensure enterprise-grade security with proper authentication authorization secrets management and compliance measures

Required Experience & Skills

Full-Stack Development (4 years)

Expert-level proficiency in Python with modern frameworks (FastAPI Flask)
Strong TypeScript/JavaScript skills with deep React and experience
Proven track record designing and building RESTful and GraphQL APIs
Solid understanding of relational (PostgreSQL MySQL) and NoSQL (MongoDB) databases
Experience with authentication systems (OAuth2 JWT SSO) and security best practices
Track record of shipping high-quality scalable software to production

AI/ML Engineering (3 years)

Hands-on experience building and deploying AI/ML applications in production environments
Deep understanding of LLM integration prompt engineering and context management
Proven expertise with RAG systems: document processing chunking embedding retrieval and generation
Experience working with vector databases (Pinecone Weaviate Chroma FAISS or Qdrant)
Strong grasp of semantic search similarity algorithms and hybrid search techniques
Knowledge of evaluation frameworks for assessing AI system quality and performance

MLOps & Infrastructure (3 years)

Production experience with Docker containerization and Kubernetes orchestration
Strong knowledge of at least one major cloud platform (AWS Azure or GCP) and their AI services
Experience building CI/CD pipelines for ML/AI applications
Proficiency with infrastructure as code tools (Terraform CloudFormation Pulumi)
Understanding of monitoring logging and alerting best practices
Cost optimization experience for cloud and AI workloads

Software Engineering Excellence

Strong computer science fundamentals and algorithmic thinking
Experience with test-driven development (TDD) and comprehensive testing strategies
Proficiency with Git workflows code review practices and collaborative development
Excellent debugging and problem-solving skills
Clear technical communication and documentation abilities
Agile/Scrum experience with ability to work in fast-paced environments

Qualifications :

Preferred Qualifications
Advanced AI Capabilities

Experience with LangChain LlamaIndex LangGraph or similar LLM frameworks
Knowledge of fine-tuning techniques (LoRA QLoRA) and parameter-efficient methods
Familiarity with agent architectures tool-using systems and Model Context Protocol (MCP)
Experience with multi-modal AI (vision-language models document understanding)
Background in prompt optimization structured outputs and function calling

Extended Technical Skills

Additional programming languages: Go Rust or backend experience
Advanced Kubernetes knowledge: Helm operators service mesh (Istio)
Experience with message queues (Kafka RabbitMQ AWS SQS) and event-driven architectures
Knowledge of graph databases (Neo4j) for advanced memory systems
Contributions to open-source AI/ML projects

Leadership & Collaboration

Experience mentoring junior engineers and conducting technical interviews
Track record of making impactful architectural decisions
Ability to translate complex technical concepts for non-technical stakeholders
Experience working across teams (product design data science)

Additional Information :

All your information will be kept confidential according to EEO guidelines.

Remote Work :

Employment Type :

Full-time

OverviewWere seeking an exceptional Full Stack Engineer to build and scale our enterprise AI applications. Youll design and implement complete AI-powered features from database to UI working with cutting-edge LLM technology RAG systems and production ML infrastructure. This role combines full-stack ...