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AI​/ML Engineer

Job in Dallas, Dallas County, Texas, 75201, USA
Listing for: ENSEK
Full Time position Listed on 2026-11-07
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer, AI Reliability/ Performance Engineer
Salary/Wage Range or Industry Benchmark: 150000 - 230000 USD Yearly USD 150000.00 230000.00 YEAR

Job Description & How to Apply Below

Описание: ENSEK builds the cloud‑native SaaS software that’s transforming how energy retailers operate, innovate and manage  help retailers lower operating costs, improve billing accuracy for consumers, and enhance customer experience through automation and AI‑driven insight, all underpinned by modern, cloud‑native architecture. ENSEK is at an exciting inflection point as we scale at pace towards new international horizons. If you’re driven by solving complex, real‑world problems and want to build modern technology that accelerates the global energy transition, you’ll feel right at home with us.

We're looking for a Staff AI/ML Engineer to become the founding technical lead for ENSEK's AI/ML Platform. This is a unique opportunity to shape a new strategic capability from the ground up.

Задачи:
  • Lead the architecture, technical strategy and roadmap for ENSEK's AI/ML Platform, evolving it into a scalable capability used across multiple product domains.
  • Design and build production-ready golden paths for Machine Learning, GenAI and Agentic AI solutions.
  • Establish standards for model lifecycle management, prompt versioning, deployment, serving, retrieval‑augmented generation (RAG), orchestration and secure tool access.
  • Build robust MLOps and LLMOps capabilities, including evaluation frameworks, experimentation tooling, observability, monitoring and cost management.
  • Create and maintain registries for AI products, models and prompts to ensure visibility, governance and operational excellence.
  • Partner closely with Data Scientists to ope rationalise machine learning models, GenAI applications and agentic workflows into reliable production services.
  • Define patterns for human‑in‑the‑loop workflows, confidence‑based routing and AI safety mechanisms.
  • Embed security, governance, compliance and responsible AI practices into the platform from day one.
  • Collaborate with Legal, Cyber Security, Risk and Product teams to ensure AI solutions remain safe, explainable and auditable within regulated environments.
  • Mentor ML Engineers and other developers across the organisation while helping establish engineering standards and best practices.
  • Contribute to the long‑term growth, structure and operating model of ENSEK's AI Engineering capability.

Key outcomes:

  • The platform's first AI-powered capabilities are running successfully in production and delivering measurable business value.
  • Multiple product teams are building, deploying and operating AI solutions through the platform's approved patterns and tooling.
  • AI products are consistently governed, observable and measurable through standardised evaluation, monitoring and reporting.
  • Every production AI capability is registered, auditable and supported by appropriate safety guardrails.
  • Teams have clear guidance on model selection, hosting approaches and platform capabilities.
  • The platform becomes the preferred route for AI innovation across ENSEK rather than teams developing isolated solutions.
  • A high‑performing ML Engineering team is established with strong engineering practices and a close partnership with Data Science.
Требования:
  • Significant experience as an AI Engineer, ML Engineer, Software Engineer or Technical Lead delivering production Machine Learning and AI solutions.
  • Experience operating at Staff Engineer, Principal Engineer or equivalent technical leadership level.
  • Deep expertise in MLOps and production machine learning platforms, including model deployment, serving, monitoring, evaluation and lifecycle management.
  • Proven experience building and operating applications powered by Large Language Models (LLMs).
  • Strong hands‑on experience with Retrieval‑Augmented Generation (RAG), prompt engineering, evaluation frameworks and agentic AI workflows.
  • Excellent software engineering…
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