Sr. Engineer(Agentic AI)
Why This Role Stands Out
This hybrid Sr. Engineer role offers a fantastic opportunity to lead cutting-edge Agentic AI development with strong compensation. You'll thrive here if you have a proven track record in building production-grade AI applications and a passion for pushing the boundaries of AI technology. Apply now to join a dynamic team and make a significant impact!
Quick Overview
Job Description
Job Title: Sr. Engineer(Agentic AI)
Location: Dallas,TX
Duration: 6 Months + Extension
Bill Rate: $73/hour
Job Type: C2C/1099 Contract
Client: To Be Discussed Later
Work Authorization: US-Citizen, H-1B, OPT-EAD, GC-EAD
Job Description
Core Technical Skills
- 5 6 years of experience in Core Application Engineering
- Must completed DOJO course (Only for internal candidate)
- Minimum 2 years of hands-on experience in Agentic AI Engineering
- Delivered at least 2 production-grade Agentic AI applications as an Engineer
- Strong understanding of: Agentic AI, Multi-Agent Systems, AI Workflows, Agent Orchestration, MCP (Model Context Protocol)
- Hands-on experience with: LangGraph, LangChain, CrewAI & AutoGen (Good to Have)
- Strong experience in: Prompt Engineering, RAG Architecture, AI Observability, AI Testing & Evaluation, LLM Fine-Tuning Concepts, Tool Calling & Function Calling
- Backend Development: Python, FastAPI / Flask, REST API Development
- Frontend Development: React, TypeScript / JavaScript, CSS
- Experience with: Docker, Kubernetes, CI/CD Pipelines, GitHub / Azure DevOps, Azure Cloud Services (Document intelligence, Azure Vision, Cognitive Services etc..)
- Database & Infrastructure: PostgreSQL / MongoDB, Redis, Vector Databases (ChromaDB, Pinecone, FAISS)
Key Responsibilities
- Design and develop enterprise-grade Agentic AI applications
- Build and orchestrate AI agents using LangGraph and LangChain
- Develop scalable backend services using Python/FastAPI
- Build responsive frontend applications using React
- Develop multi-agent workflows with planning, memory, and tool integration
- Implement RAG-based architectures and vector search solutions
- Integrate LLMs with enterprise APIs, tools, and databases
- Implement AI observability, tracing, monitoring, and evaluation
- Perform prompt optimization and model performance tuning
- Create reusable AI workflow and orchestration components
- Work closely with Architects, Product Teams, and Platform Engineers
- Ensure scalability, reliability, and security of AI applications
Equal Opportunity Employer:
We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law
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