AI Engineer - Dallas, TX(Onsite)

Role: AI Engineer
Location: Dallas, TX(Onsite)

Looking For W2 No C2C

Software Engineering & System Design:

• Write, test, and deploy production-quality code with a strong focus on scalability and performance.
• Design and implement end-to-end systems including API, database, and application layers.
• Consider memory usage, performance optimization, and modular architecture in code design.
• Follow modern DevOps practices for deployment and environment management.
• Python Development
• Write clean, modular Python code with proper environment management (virtualenv, poetry, conda).
• Build and deploy RESTful APIs using frameworks like FastAPI or Flask.
• Connect applications to relational and NoSQL databases.
• Containerize applications using Docker and deploy in Kubernetes / cloud environments.

Database Skills:

• Write and optimize SQL and PL/SQL queries for data retrieval and transformation.
• Integrate database logic effectively into application workflows.
• Generative AI Development
• Understand how Large Language Models (LLMs) work - architecture, limitations, and tuning methods.

Design and implement RAG (Retrieval-Augmented Generation) systems:

• Build pipelines connecting vector databases, LLMs, and application layers.
• Optimize retrieval and response accuracy through prompt engineering and context management.
• Apply best practices and advanced RAG techniques (chunking strategies, caching, query re-ranking).
• Develop and manage prompt templates, parameter configurations, and evaluation metrics.
• Agentic AI Systems
• Understand AI agents, their lifecycle, and how they integrate with tools and APIs.
• Implement tool calling and human-in-the-loop workflows.
• Design multi-agent architectures using frameworks such as LangChain or LangGraph.
• Apply agent orchestration best practices, ensuring reliability, observability, and control.

Required Skills & Qualifications:

• Strong understanding of software design principles and ability to think like a developer (language agnostic).
• Proficiency in Python with good exposure to building APIs, database integration, and container-based deployment.
• Working knowledge of SQL / PL-SQL for querying and joining data.
• Experience in developing or integrating GenAI or RAG-based systems using OpenAI, Anthropic, or similar models.
• Familiarity with LangChain, LangGraph, or similar frameworks for AI workflow orchestration.
• Any experience with Servicenow background or platform like ITSM, CMDB, CSA, CAD, CIS.
• Strong debugging, optimization, and analytical skills.
• Excellent communication and collaboration abilities in a fast-paced environment.

Nice to Have:

• Exposure to cloud platforms (AWS, Google Cloud Platform, Azure) for AI workload deployment.
• Experience with vector databases (FAISS, Pinecone, Weaviate, or Chroma).
• Knowledge of monitoring and observability tools for AI systems.
• Familiarity with CI/CD pipelines, GitOps, and infrastructure automation.

Best Regards:

Peerbhi SK
Phone:
Email: