Python AI Engineer

Overview

Remote
Depends on Experience
Accepts corp to corp applications
Contract - W2
Contract - Independent

Skills

Python integrate with API development skills
Agentic AI
Data Storage & Modeling
AWS (no azure)

Job Details

Job Description

  • Technical Skills:
    • Python Engineering: Strong experience building backend services, AI workloads, orchestration layers, and agentic systems using Python.
    • .NET/C# Systems Integration: Skilled in developing enterprise-grade APIs and service layers using .NET/C#, including secure integration with internal platforms.
    • Front-End Development: Proficient with Angular and TypeScript for building modern, scalable, and user-friendly front-end applications.
    • AI & LLM Engineering: Hands-on experience with LLMs, prompt engineering, vector search, embeddings, evaluation techniques, and multi-step workflows.
    • Agentic Architectures: Familiar with enterprise agent frameworks and tools such as LangChain, LangGraph, and LangSmith for designing, observing, and optimizing AI workflows.
    • Data Storage & Modeling: Practical experience with Snowflake (analytics workloads), SQL (schema design & querying), MongoDB (document storage), and Neo4j (graph reasoning).
    • Event Streaming: Knowledge of Kafka for event-driven communication and real-time system processing.
    • Cloud Deployment: Capable of designing and deploying full-stack AI solutions across AWS (primary), with additional exposure to Azure and Google Cloud Platform.
    • API Lifecycle Management: Experience using Azure APIM for API management, governance, and secure platform integration.
    • Infrastructure & DevOps Awareness: Comfortable with hosting, scaling, CI/CD best practices, authentication/authorization, and secure deployment patterns in enterprise environments.
  • Soft Skills:
    • End-to-End Ownership: Able to independently architect, implement, and deliver complete AI-driven applications across the full vertical stack.
    • Product & Technical Communication: Communicates clearly, proactively, and respectfully; provides technical recommendations with clear options and tradeoffs.
    • Cross-Functional Collaboration: Works effectively with product, engineering, and business stakeholders; listens deeply before shaping solutions.
    • Consultative Mindset: Brings clarity in ambiguous situations, offers guidance, and helps drive decision-making with well-reasoned technical insight.
    • Adaptability: Quickly ramps up in unfamiliar domains and remains effective amid evolving priorities or strategic pivots.
    • Knowledge Sharing: Elevates internal engineering teams by openly sharing expertise in AI systems, data modeling, cloud patterns, and platform best practices.
    • Quality & Velocity: Delivers tangible outcomes quickly while maintaining a high standard of engineering quality, reliability, and maintainability.
    • Direct & Constructive Dialogue: Comfortable giving and receiving candid feedback and iterating to improve solutions, processes, and team cohesion.

Roles & Responsibilities

  • Technical Skills:
    • Python Engineering: Strong experience building backend services, AI workloads, orchestration layers, and agentic systems using Python.
    • .NET/C# Systems Integration: Skilled in developing enterprise-grade APIs and service layers using .NET/C#, including secure integration with internal platforms.
    • Front-End Development: Proficient with Angular and TypeScript for building modern, scalable, and user-friendly front-end applications.
    • AI & LLM Engineering: Hands-on experience with LLMs, prompt engineering, vector search, embeddings, evaluation techniques, and multi-step workflows.
    • Agentic Architectures: Familiar with enterprise agent frameworks and tools such as LangChain, LangGraph, and LangSmith for designing, observing, and optimizing AI workflows.
    • Data Storage & Modeling: Practical experience with Snowflake (analytics workloads), SQL (schema design & querying), MongoDB (document storage), and Neo4j (graph reasoning).
    • Event Streaming: Knowledge of Kafka for event-driven communication and real-time system processing.
    • Cloud Deployment: Capable of designing and deploying full-stack AI solutions across AWS (primary), with additional exposure to Azure and Google Cloud Platform.
    • API Lifecycle Management: Experience using Azure APIM for API management, governance, and secure platform integration.
    • Infrastructure & DevOps Awareness: Comfortable with hosting, scaling, CI/CD best practices, authentication/authorization, and secure deployment patterns in enterprise environments.
  • Soft Skills:
    • End-to-End Ownership: Able to independently architect, implement, and deliver complete AI-driven applications across the full vertical stack.
    • Product & Technical Communication: Communicates clearly, proactively, and respectfully; provides technical recommendations with clear options and tradeoffs.
    • Cross-Functional Collaboration: Works effectively with product, engineering, and business stakeholders; listens deeply before shaping solutions.
    • Consultative Mindset: Brings clarity in ambiguous situations, offers guidance, and helps drive decision-making with well-reasoned technical insight.
    • Adaptability: Quickly ramps up in unfamiliar domains and remains effective amid evolving priorities or strategic pivots.
    • Knowledge Sharing: Elevates internal engineering teams by openly sharing expertise in AI systems, data modeling, cloud patterns, and platform best practices.
    • Quality & Velocity: Delivers tangible outcomes quickly while maintaining a high standard of engineering quality, reliability, and maintainability.
    • Direct & Constructive Dialogue: Comfortable giving and receiving candid feedback and iterating to improve solutions, processes, and team cohesion.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.