Artificial Intelligence Engineer Architect

We are looking for an AI Engineer location is Dallas, TX Remote work, if you're interested, please share updated resume

Job Title: AI Engineer Python integrate with API development

Location: Dallas, TX Remote

Longterm contract

Skills:

Agentic ai

Python integrate with API development
Data Storage & Modeling: AWS (no azure)

Mandatory Skills: Python, Angular, TypeScript, LLMs, Azure AI Foundry, Azure OpenAI, GenAI, Machine Learning, SQL, Langchain, Neo4j

Job Description

• Technical Skills:

o Python Engineering: Strong experience building backend services, AI workloads, orchestration layers, and agentic systems using Python.

o .NET/C# Systems Integration: Skilled in developing enterprise-grade APIs and service layers using .NET/C#, including secure integration with internal platforms.

o Front-End Development: Proficient with Angular and TypeScript for building modern, scalable, and user-friendly front-end applications.

o AI & LLM Engineering: Hands-on experience with LLMs, prompt engineering, vector search, embeddings, evaluation techniques, and multi-step workflows.

o Agentic Architectures: Familiar with enterprise agent frameworks and tools such as LangChain, LangGraph, and LangSmith for designing, observing, and optimizing

AI workflows.

o Data Storage & Modeling: Practical experience with Snowflake (analytics workloads), SQL (schema design & querying), MongoDB (document storage), and Neo4j (graph reasoning).

o Event Streaming: Knowledge of Kafka for event-driven communication and real-time system processing.

o Cloud Deployment: Capable of designing and deploying full-stack AI solutions across AWS (primary), with additional exposure to Azure and GCP.

o API Lifecycle Management: Experience using Azure APIM for API management, governance, and secure platform integration.

o Infrastructure & DevOps Awareness: Comfortable with hosting, scaling, CI/CD best practices, authentication/authorization, and secure deployment patterns in enterprise environments.

Soft Skills:

o End-to-End Ownership: Able to independently architect, implement, and deliver complete AI-driven applications across the full vertical stack.

o Product & Technical Communication: Communicates clearly, proactively, and respectfully; provides technical recommendations with clear options and tradeoffs.

o Cross-Functional Collaboration: Works effectively with product, engineering, and business stakeholders; listens deeply before shaping solutions.

o Consultative Mindset: Brings clarity in ambiguous situations, offers guidance, and helps drive decision-making with well-reasoned technical insight.

o Adaptability: Quickly ramps up in unfamiliar domains and remains effective amid evolving priorities or strategic pivots.

o Knowledge Sharing: Elevates internal engineering teams by openly sharing expertise in AI systems, data modeling, cloud patterns, and platform best practices.

o Quality & Velocity: Delivers tangible outcomes quickly while maintaining a high standard of engineering quality, reliability, and maintainability.

o Direct & Constructive Dialogue: Comfortable giving and receiving candid feedback and iterating to improve solutions, processes, and team cohesion.

Roles & Responsibilities

• Technical Skills:

o Python Engineering: Strong experience building backend services, AI workloads, orchestration layers, and agentic systems using Python.

o .NET/C# Systems Integration: Skilled in developing enterprise-grade APIs and service layers using .NET/C#, including secure integration with internal platforms.

o Front-End Development: Proficient with Angular and TypeScript for building modern, scalable, and user-friendly front-end applications.

o AI & LLM Engineering: Hands-on experience with LLMs, prompt engineering, vector search, embeddings, evaluation techniques, and multi-step workflows.

o Agentic Architectures: Familiar with enterprise agent frameworks and tools such as LangChain, LangGraph, and LangSmith for designing, observing, and optimizing AI workflows.

o Data Storage & Modeling: Practical experience with Snowflake (analytics workloads), SQL (schema design & querying), MongoDB (document storage), and Neo4j (graph reasoning).

o Event Streaming: Knowledge of Kafka for event-driven communication and real-time system processing.

o Cloud Deployment: Capable of designing and deploying full-stack AI solutions across AWS (primary), with additional exposure to Azure and GCP.

o API Lifecycle Management: Experience using Azure APIM for API management, governance, and secure platform integration.

o Infrastructure & DevOps Awareness: Comfortable with hosting, scaling, CI/CD best practices, authentication/authorization, and secure deployment patterns in enterprise environments.

Soft Skills:

o End-to-End Ownership: Able to independently architect, implement, and deliver complete AI-driven applications across the full vertical stack.

o Product & Technical Communication: Communicates clearly, proactively, and respectfully; provides technical recommendations with clear options and tradeoffs.

o Cross-Functional Collaboration: Works effectively with product, engineering, and business stakeholders; listens deeply before shaping solutions.

o Consultative Mindset: Brings clarity in ambiguous situations, offers guidance, and helps drive decision-making with well-reasoned technical insight.

o Adaptability: Quickly ramps up in unfamiliar domains and remains effective amid evolving priorities or strategic pivots.

o Knowledge Sharing: Elevates internal engineering teams by openly sharing expertise in AI systems, data modeling, cloud patterns, and platform best practices.

o Quality & Velocity: Delivers tangible outcomes quickly while maintaining a high standard of engineering quality, reliability, and maintainability.

o Direct & Constructive Dialogue: Comfortable giving and receiving candid feedback and iterating to improve solutions, processes, and team cohesion.