Tech Lead – AI Software Engineering & Productivity

Open 35d posting dated 2 weeks ago

Industry: debt collection

Remote work: 100%

Project language: English

FTE: full-time

Project length: 6 months + prolongations

Start: ASAP

Assignment type: B2B

Summary: This role focuses on leading the integration of AI in software engineering to enhance developer productivity, software quality, and process efficiency across the organization.

Main Responsibilities:

  • Define and execute the organization's strategy for AI-assisted software engineering.

  • Identify opportunities to leverage AI for improving developer productivity and software quality.

  • Lead the selection and implementation of AI engineering tools and platforms.

  • Drive the adoption of generative AI across engineering teams.

  • Provide technical leadership for AI-enabled development solutions.

  • Establish engineering standards and best practices for AI-assisted development.

  • Collaborate with teams to integrate AI into existing workflows.

  • Measure and improve engineering productivity through data-driven initiatives.

  • Develop internal AI-powered tools and enhance automation frameworks.

  • Partner with cross-functional teams for seamless AI adoption.

  • Establish guardrails for secure AI usage and monitor AI solution performance.

Key Requirements:

  • Bachelor's or Master's degree in Computer Science or a related field.

  • 8+ years of software engineering experience.

  • 5+ years in a technical leadership role.

  • Strong experience with modern software engineering practices and cloud platforms.

  • Experience in AI/ML or Generative AI solutions.

  • Deep understanding of the software development lifecycle.

  • Programming skills in Python, Java, C#, TypeScript, or Go.

  • Experience with APIs, microservices, and platform engineering.

Nice to Have:

  • Experience with Large Language Models and prompt engineering.

  • Familiarity with AI frameworks like LangChain and LlamaIndex.

  • Experience with GitHub Copilot and AI coding tools.

  • Knowledge of MLOps and AI governance practices.

  • Cloud or AI-related certifications.