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 GCP 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: 1-
Email:
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. Co...
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 GCP 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: 1-
Email:
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