Platform Lead / Architect - AI Platform Engineering

PMTS LLC
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Remote

Tech stack

API
Artificial Intelligence
Amazon Web Services (AWS)
Application Integration Architecture
Computing Platforms
Azure
Cloud Computing
Cloud Engineering
Computer Programming
Continuous Integration
DevOps
Distributed Systems
Github
Monitoring of Systems
Identity and Access Management
Python
OAuth
Openid Connect
Prometheus
Software Engineering
Systems Integration
Strategies of Testing
Web Platforms
Workflow Management Systems
Datadog
Data Logging
Google Cloud Platform
Large Language Models
Grafana
Multi-Agent Systems
Generative AI
Infrastructure as Code (IaC)
Backend
Cloudformation
FastAPI
Event Driven Architecture
Containerization
AI Platforms
Kubernetes
Enterprise Integration
Operational Systems
Virtual Agents
REST
Terraform
Docker
Jenkins
Microservices

Job description

Photon is seeking a highly experienced Platform Lead / Architect - AI Platform Engineering to lead the architecture, design, and delivery of Tulip AI, a unified AI-powered employee support platform.

Tulip AI is an enterprise-grade AI platform that streamlines employee support across frontline and headquarters teams through a single AI-driven experience. The platform leverages Generative AI, workflow orchestration, enterprise integrations, automation, and cloud-native technologies to improve operational efficiency and accelerate issue resolution., * Lead the overall architecture, technical strategy, and solution design for Tulip AI and related digital platforms.

  • Design and deliver scalable, secure, resilient, and cloud-native enterprise solutions.
  • Architect backend services, APIs, and microservices using Python and FastAPI.
  • Drive implementation of Generative AI, agentic AI capabilities, workflow orchestration, and intelligent automation solutions.
  • Design enterprise integration architectures connecting HR, IT, identity management, operational systems, and third-party platforms.
  • Define and enforce standards for APIs, microservices, event-driven systems, and integration patterns.
  • Collaborate with Product, Engineering, UX, and Business stakeholders to align technical solutions with business objectives.
  • Support product roadmap planning, backlog prioritization, and Agile delivery processes.
  • Establish engineering best practices around scalability, performance, security, observability, monitoring, and reliability.
  • Drive adoption of AI-assisted development, automation, and engineering productivity tools.
  • Provide technical leadership, architectural governance, and mentorship across engineering teams.
  • Lead cloud deployment strategies leveraging Kubernetes, CI/CD pipelines, Infrastructure as Code (IaC), and DevOps practices.
  • Ensure production readiness through testing strategies, monitoring, logging, and operational excellence., Programming & Backend
  • Python
  • FastAPI
  • REST APIs
  • Microservices

AI & Automation

  • Generative AI
  • Agentic AI
  • AI Orchestration Frameworks
  • Workflow Automation
  • LLM Integrations
  • RAG Architectures

Cloud & Infrastructure

  • AWS / Azure / Google Cloud Platform
  • Kubernetes
  • Docker
  • Terraform
  • Infrastructure as Code

DevOps

  • CI/CD
  • GitHub Actions
  • Jenkins
  • Azure DevOps
  • Monitoring & Observability

Architecture

  • Enterprise Architecture
  • Distributed Systems
  • Event-Driven Architecture
  • Integration Architecture

Requirements

The ideal candidate will have deep expertise in enterprise architecture, AI platforms, cloud-native systems, distributed architectures, Python-based backend development, and platform engineering. This role requires strong technical leadership and the ability to drive architectural decisions across multiple engineering teams., * 12+ years of experience in Software Engineering, Platform Architecture, Enterprise Architecture, or Solution Architecture.

  • Strong expertise in Python development and FastAPI-based microservices architecture.
  • Extensive experience designing and implementing cloud-native enterprise platforms.
  • Hands-on experience with Generative AI, AI orchestration frameworks, AI agents, workflow automation, and enterprise AI solutions.
  • Strong understanding of:
  • Microservices Architecture
  • REST APIs
  • Event-Driven Systems
  • Integration Architecture
  • Experience with one or more cloud platforms:
  • AWS
  • Microsoft Azure
  • Google Cloud Platform (Google Cloud Platform)
  • Expertise in:
  • Kubernetes
  • Docker/Containerization
  • CI/CD Pipelines
  • DevOps Practices
  • Infrastructure as Code (Terraform, CloudFormation, etc.)
  • Strong knowledge of:
  • Enterprise Security
  • Authentication & Authorization
  • OAuth2/OpenID Connect
  • Secure API Design
  • Experience working in Agile/Scrum environments.
  • Excellent communication, stakeholder management, and technical leadership skills., * Experience building enterprise-scale AI platforms and digital employee experience solutions.
  • Familiarity with AI frameworks such as LangChain, LangGraph, Semantic Kernel, CrewAI, AutoGen, or similar orchestration platforms.
  • Experience with vector databases, RAG architectures, LLM integrations, and AI governance frameworks.
  • Experience implementing observability solutions using Prometheus, Grafana, Datadog, OpenTelemetry, or similar tools.
  • Prior experience leading distributed engineering teams and large-scale transformation initiatives.

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