Full Stack Engineer - Enterprise AI

Full Stack Engineer - Enterprise AI Applications

Experience Level: Mid Level 4+ years

Work Authorization/Clearance Requirements: NA

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.

• 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

• Build scalable backend services with Python/FastAPI
• Develop performant UIs in React/Next.js with real‑time LLM streaming
• Design optimized databases across Postgre
  
  SQL, Mongo
  
  DB, Redis
• Implement Web Sockets, event‑driven systems, and comprehensive test coverage

• Build CI/CD pipelines for rapid, reliable releases
• Manage IaC with Terraform on AWS/Azure/GCP
• Set up monitoring/observability (Datadog, Prometheus, Lang Smith, W&B)
• Ensure security best practices and cost‑efficient AI operations

• Strong Python (FastAPI/Flask) and Type Script/React/Next.js
• REST/Graph
  
  QL API design, authentication, and security best practices
• Experience with relational & No
  
  SQL databases
• Proven delivery of scalable production systems
• 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
• Docker, Kubernetes, CI/CD for ML workloads
• Cloud platforms (AWS/Azure/GCP) and IaC (Terraform/Pulumi)
• Monitoring, logging, alerting, and cost optimization
• Strong CS fundamentals, problem‑solving, debugging
• Comfortable in fast‑paced Agile environments

• Experience with Lang Chain, Llama Index, Lang Graph, agent frameworks
• Exposure to LoRA/QLoRA fine‑tuning, multimodal AI, MCP
• Experience with Kafka/Rabbit
  
  MQ, graph DBs (Neo4j)
• Open‑source contributions
• Python, Pandas, ML/DL/NLP/GPT‑based workflows
• OpenAI, Hugging Face, Claude, Cohere, Mistral
• Agentic AI (Lang Graph, CrewAI, Auto Gen, Lang Chain Agents)

Seniority level: Mid‑Senior level

Employment type: Full‑time

Job function: Information Technology

Industries: IT Services and IT Consulting and Software Development

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