What are the responsibilities and job description for the Full Stack Engineer - Enterprise AI Applications position at Oteemo Inc.?
Full Stack Engineer - Enterprise AI Applications
Experience Level: Mid Level 4 years
Location: Richmond, VA (Hybrid)
Work Authorization/Clearance Requirements: NA
Roles and Responsibilities of this position:
Overview
We're seeking an exceptional Full Stack Engineer to build and scale our enterprise AI applications. You'll 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.
You'll 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 You’ll Build
AI Applications
- Design end-to-end RAG pipelines for intelligent search and enterprise Q&A
- Integrate production-grade LLM solutions (GPT-4, Claude, Gemini)
- Develop prompt strategies, evaluation frameworks, and structured output workflows
- Build autonomous agents with tool-use capabilities
- Implement vector search using Pinecone, Weaviate, Chroma, FAISS, or Qdrant
Full-Stack Features
- Build scalable backend services with Python/FastAPI
- Develop performant UIs in React/Next.js with real-time LLM streaming
- Design optimized databases across PostgreSQL, MongoDB, Redis
- Implement WebSockets, event-driven systems, and comprehensive test coverage
Production Infrastructure
- Deploy AI services using Docker & Kubernetes
- Build CI/CD pipelines for rapid, reliable releases
- Manage IaC with Terraform on AWS/Azure/GCP
- Set up monitoring/observability (Datadog, Prometheus, LangSmith, W&B)
- Ensure security best practices and cost-efficient AI operations
Required Experience
Full-Stack Development (4 yrs)
- Strong Python (FastAPI/Flask) and TypeScript/React/Next.js
- REST/GraphQL API design, authentication, and security best practices
- Experience with relational & NoSQL databases
- Proven delivery of scalable production systems
AI/ML Engineering (3 yrs)
- Hands-on LLM integration, prompt engineering, and context management
- Strong experience with RAG (chunking, embeddings, retrieval, generation)
- Proficiency with vector DBs and semantic/hybrid search
- Knowledge of AI evaluation frameworks
MLOps & Cloud (3 yrs)
- Docker, Kubernetes, CI/CD for ML workloads
- Cloud platforms (AWS/Azure/GCP) and IaC (Terraform/Pulumi)
- Monitoring, logging, alerting, and cost optimization
Engineering Excellence
- Strong CS fundamentals, problem-solving, debugging
- TDD, Git workflows, code reviews, clean documentation
- Comfortable in fast-paced Agile environments
Preferred Qualifications
- Experience with LangChain, LlamaIndex, LangGraph, agent frameworks
- Exposure to LoRA/QLoRA fine-tuning, multimodal AI, MCP
- Experience with Kafka/RabbitMQ, graph DBs (Neo4j)
- Open-source contributions
- Mentorship, architectural decision-making, cross-team collaboration
Tech Stack Exposure (Preferred)
- Python, Pandas, ML/DL/NLP/GPT-based workflows
- OpenAI, HuggingFace, Claude, Cohere, Mistral
- Agentic AI (LangGraph, CrewAI, AutoGen, LangChain Agents)
- Docker, Kubernetes, Git, CI/CD