AI Native Development lead/ Architect

Tror AI for everyone

Atlanta, GA

JOB DETAILS
SKILLS
Amazon Web Services (AWS), Application Programming Interface (API), Artificial Intelligence (AI), Automation, Best Practices, Cloud Computing, Coaching, Code Reviews, Coding Standards, Communication Skills, Continuous Deployment/Delivery, Continuous Integration, Cryptography, Data Analysis, Data Management, Data Quality, DevOps, Docker, GitHub, IP (Internet Protocol), Leadership, Mentoring, Metrics, Microservices, Microsoft .NET, Microsoft C# (C Sharp), Network Architecture/Engineering, Productivity Management, Programming Tools, Prototyping, Python Programming/Scripting Language, Quality Assurance Methodology, Security Infrastructure, Service Level Agreement (SLA), Team Building, Technical Writing, Threat Modeling, Validation Testing
LOCATION
Atlanta, GA
POSTED
9 days ago

Job Role: AI Native Development lead/ Architect

Job Location: Atlanta, GA (Hybrid)

Job Type: Contract

Role Summary
We are looking for an AI Native Development Architect to design and guide the build of cloud-native, data- and AI-driven applications on AWS. You will define target architectures, enable engineering teams with reusable patterns and reference implementations, and accelerate delivery using modern AI-assisted development tools.

Key Responsibilities

  • Define end-to-end architecture for AI-native products, including application, data, integration, security, and operations on AWS.
  • Lead design reviews and provide technical direction across Python and C#/.NET codebases.
  • Architect data pipelines and analytical workloads using PySpark and AWS Glue; establish standards for data quality, lineage, and observability.
  • Design and implement scalable APIs and microservices using FastAPI (and/or .NET Web APIs) with clear contracts, versioning, and performance SLAs.
  • Establish reference architectures for LLM/RAG-enabled capabilities (e.g., retrieval patterns, prompt management, evaluation, guardrails) aligned with organizational policies.
  • Partner with Security, Platform, and DevOps teams to implement secure-by-design practices (IAM, secrets, network controls, encryption, threat modeling).
  • Define CI/CD, branching, testing, and release practices; improve developer productivity with automation and paved-road templates.
  • Champion AI-assisted engineering workflows using tools such as GitHub Copilot, Cursor, and Claude AI while ensuring code quality and compliance.
  • Mentor engineers, create technical documentation, and drive adoption of best practices across teams.

Required Skills:

  • Python: strong hands-on experience building services and data workloads using Python, PySpark, AWS Glue, and FastAPI.
  • C#/.NET: ability to design and review .NET services and libraries; familiarity with modern .NET runtime and patterns.
  • AWS: strong understanding of AWS architecture fundamentals (networking, IAM, compute, storage, managed services) and designing for scale, reliability, and cost.

AI Native Development Tools

  • Proficiency using AI coding assistants to accelerate development while maintaining engineering rigor: GitHub Copilot, Cursor, Claude AI.
  • Ability to establish team guidelines for AI-assisted coding (review standards, secure prompting, IP/compliance awareness, and validation/testing).

Preferred Qualifications

  • Experience designing GenAI solutions (RAG, tool/function calling, agents) and implementing evaluation/monitoring approaches.
  • Experience with infrastructure as code (e.g., CloudFormation/CDK/Terraform) and container platforms (Docker/ECS/EKS).
  • Knowledge of MLOps patterns (model lifecycle, feature stores, experiment tracking) and data governance concepts.
  • Strong understanding of observability practices (logs/metrics/traces) and SRE-oriented reliability design.

Soft Skills & Competencies

  • Architecture leadership: can balance short-term delivery with long-term platform thinking.
  • Clear communication: can translate complex technical decisions for engineering and business stakeholders.
  • Hands-on mindset: comfortable prototyping and jumping into code to unblock teams.
  • Quality and security focus: promotes testing discipline, secure coding, and operational readiness.
  • Collaboration and mentorship: builds alignment, coaches engineers, and scales best practices across squads.


About the Company

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Tror AI for everyone