Senior AI Engineer/Team Lead

Full Description

Summary

We are looking for a Senior AI Engineer who will be responsible for developing and deploying scalable AI-powered systems and agentic workflows. This role requires a blend of AI expertise and software engineering skills to achieve business objectives. Key responsibilities include working with programming languages like Python and C#/.NET, cloud platforms (AWS/Azure), and infrastructure ascode tools (Terraform). The engineer will also focus on AI and LLM operations, utilizing models like OpenAI GPT-4 and Anthropic Claude, frameworks like LangChain/LangGraph and AutoGen, and implementing techniques such as prompt engineering, model fine-tuning, and agentic workflow orchestration. Experience with data systems including SQL Server/PostgreSQL and vector databases, along with platform skills in RESTful APIs, CI/CD, MLOps, and Docker, is essential. Proficiency in operations such as monitoring, logging, debugging, and systems optimization is also required.

Must Have

• Python, Pydantic, C#/.NET 6+

• Cloud platforms (AWS/Azure)

• Git/GitHub, Terraform

• OpenAI GPT-4, LangChain/LangGraph

• AutoGen, prompt engineering

• Model fine-tuning, agentic workflows

• SQL Server/PostgreSQL, vector databases

• RESTful APIs, CI/CD, MLOps

• Docker, monitoring, logging, debugging

Good To Have

• Anthropic Claude

• Cost monitoring & FinOps

• API rate limiting

• Real-time data processing

We are seeking an exceptional Senior AI Engineer to join our team. Title determined based on the applicants experience and capabilities and qualifications. This role combines deep technical AI expertise with practical software engineering, focusing on delivering scalable AI-powered systems and agentic workflows that drive measurable business outcomes.

Required Technical Skills

Programming & Infrastructure: Python, Pydantic, C#/.NET 6+, Cloud platforms (AWS/Azure), Git/GitHub), infrastructure as code (Terraform)

AI & LLM Operations: OpenAI GPT-4, Anthropic Claude, LangChain/LangGraph, AutoGen, token optimization, prompt engineering, model fine-tuning, agentic workflow orchestration, cost monitoring & FinOps, API rate limiting

Data Systems: SQL Server/PostgreSQL, vector databases, real-time data processing

Platform: RESTful APIs, CI/CD, MLOps, Docker or similar

Operations: Monitoring, logging, debugging, and systems optimization