AI Engineer
Core
Design and deploy AI automation solutions using LLMs, generative AI, and MCP servers to integrate enterprise systems and workflows.
Role type
AI Engineer (LLM & Automation)
Builds
AI agents, automation pipelines, orchestration flows, and integrations with enterprise systems, APIs, and databases.
Domain
Enterprise AI, Cloud Infrastructure, Data Engineering
Deliverable
production ML models | product features | infrastructure
Required skills
LLMs (OpenAI, Claude, Gemini, Llama, Mistral), Prompt Engineering, MCP Server Development, Python, SQL, AWS Cloud Services, AI Agents, RAG pipelines
Preferred skills
LangChain, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, FastAPI, Amazon Bedrock, CI/CD, Docker, LLM evaluation frameworks, Workflow automation tools
Technologies
Python, SQL, AWS (Neptune, Bedrock, Lambda, S3, API Gateway, CloudWatch, IAM, Step Functions, ECS, EKS, SageMaker, Glue, Athena, OpenSearch), MCP, FastAPI, LangChain, LlamaIndex, CrewAI, Airflow, n8n
Responsibilities
Design, develop, and deploy AI automation solutions using LLMs and generative AI technologies; Build, configure, and integrate Model Context Protocol (MCP) servers and tools; Develop prompt engineering strategies for production-grade AI workflows; Create AI agents, automation pipelines, and orchestration flows; Build integrations with enterprise systems, APIs, databases, and cloud services; Design, load, and query knowledge graphs using AWS Neptune or other graph databases; Develop backend logic, data pipelines, and automation scripts using Python; Write and optimize SQL queries for data extraction, validation, transformation, and reporting; Apply basic machine learning concepts including classification, regression, clustering, feature engineering, and model evaluation; Support deployment, monitoring, testing, troubleshooting, and documentation of AI automation solutions; Ensure AI solutions are secure, scalable, explainable, maintainable, and aligned with enterprise standards.
Seniority
Mid-Senior, hands-on IC