Platform Engineer

Search Services; Houston (TX); On-site; USD 140,000 - 180,000; Full time

Job summary

Our Client seeks a Senior Software & Platform Engineer to lead development of its energy intelligence platform. You will unite cloud infra, data, forecasting, AI workflows and customer apps into a secure, scalable platform.

Reporting to the Acting CTO, you will guide day-to-day engineering, code reviews, CI/CD and architectural decisions while mentoring teams across product and data domains.

Qualifications

• Strong software and platform engineering experience.
• Python proficiency with API frameworks (FastAPI or equivalent).
• PostgreSQL/PostGIS and SQL proficiency including REST APIs.
• GIT, Docker and containerized deployments.
• Strong systems thinking and software architecture skills.
• Ability to translate business requirements into scalable technical solutions.
• Excellent communication and collaboration skills.

Responsibilities

• Design and build the core cloud platform, APIs, data services, authentication and workflows.
• Modernize customer-facing apps, analytics, reporting and deployment frameworks.
• Develop canonical data models, APIs, ETL pipelines and metadata frameworks.
• Integrate forecasting, GIS, AI services and external APIs.
• Build production AI workflows for data validation and automation.
• Implement secure authentication, authorization, CEII segregation and audit logging.
• Lead engineering execution, code reviews, CI/CD, Git workflows and sprint planning.
• Mentor developers and coordinate workstreams across teams.

Skills

Python

FastAPI

PostgreSQL/PostGIS

SQL

REST APIs

Git

Docker

Systems thinking

Software architecture

Business requirements to technical

Communication

Tools

Neo4j

GIS

React

TypeScript

Message queues

Job description

Our Client is seeking a Senior Software & Platform Engineer to lead the development of its next-generation energy intelligence platform.

Reporting to the Acting CTO, this person will serve as the day-to-day technical lead, bringing together cloud infrastructure, data, forecasting, AI-enabled workflows, and customer-facing applications into a secure, scalable platform.

RESPONSIBILITIES

• Design and build the core cloud platform, APIs, data services, authentication, workflows, and customer workspaces
• Modernize existing customer-facing applications, analytical products, reporting, and deployment frameworks
• Develop canonical data models, APIs, ETL pipelines, metadata frameworks, and spatial and graph database integrations
• Integrate forecasting, grid physics, benchmarking, GIS, AI services, document management, and external APIs
• Build production AI workflows for data validation, document extraction, automation, quality assurance, and human-in-the-loop review
• Implement secure authentication, authorization, CEII segregation, audit logging, encryption, secrets management, and secure APIs
• Lead day-to-day engineering execution, including code reviews, coding standards, CI/CD, Git workflows, sprint planning, and technical estimation
• Mentor developers and coordinate technical workstreams across product, data, forecasting, and engineering teams

REQUIRED QUALIFICATIONS

• Strong software and platform engineering experience
• Python
• FastAPI or similar API frameworks
• PostgreSQL/PostGIS and SQL
• REST APIs
• Git
• Docker
• Strong systems thinking and software architecture skills
• Ability to translate business requirements into scalable technical solutions
• Excellent communication and collaboration skills

PREFERRED QUALIFICATIONS

• Neo4j or other graph databases
• GIS and spatial analytics
• React and TypeScript
• Message queues and event-driven architectures
• Experience with utilities, ISOs/RTOs, energy software, infrastructure analytics, engineering software, or asset management

AI & AUTOMATION

• Experience integrating LLM APIs, agent frameworks, RAG, document processing, prompt orchestration, workflow automation, and AI-assisted quality assurance into production environments
• This role focuses on production AI integration rather than AI model development or research

WHAT SUCCESS LOOKS LIKE

• Canonical data platform and production API framework
• AI-enabled data workflows
• Secure customer authentication
• ERCOT forecasting engine integration
• Benchmarking and data governance infrastructure