GT (Global Talent) Ltd logo

AI Engineering Lead / Manager | NDA

Job Overview

Location

Europe - Remote

Job Type

Contract

Category

Software Engineering

Date Posted

June 4, 2026

Full Job Description

đź“‹ Description

  • • Lead a 6–8 week client-facing consulting engagement focused on AI-assisted software engineering and developer productivity for a US-based enterprise client.
  • • Provide technical guidance to engineering, product, and architecture teams on adopting AI tools such as Claude Code, Cursor, GitHub Copilot, and Codex to enhance software development workflows.
  • • Assess current software engineering practices and recommend improvements across people, process, and technology to increase AI maturity in engineering teams.
  • • Design and implement LLM-powered applications, including retrieval-augmented generation (RAG) pipelines and AI agent systems aligned to business outcomes.
  • • Contribute hands-on to architecture, development, and documentation of AI applications, spending approximately 20% of time on direct coding and delivery.
  • • Advise on microservice API design using REST, GraphQL, or gRPC, and ensure alignment with modern software engineering best practices including CI/CD, automated testing, and clean code standards.
  • • Translate business requirements into clear technical specifications and implementation plans for AI-driven engineering solutions.
  • • Optimize retrieval-augmented generation pipelines by addressing tokenization limits, context window constraints, hallucination risks, and model cost-performance tradeoffs.
  • • Conduct code reviews and provide feedback on software architecture, data flows, and integration patterns for AI-enhanced systems.
  • • Coach engineering teams on prompt engineering, structured prompting techniques, and model routing strategies for LLM applications.
  • • Collaborate with consulting stakeholders and client-side teams across product, design, and platform functions to drive adoption of AI engineering practices.
  • • Maintain strong communication with both technical and non-technical stakeholders to articulate complex AI concepts and engineering tradeoffs.
  • • Work with overlapping hours to accommodate US-based client schedules during the engagement period.
  • • Support the implementation of developer productivity tooling and internal developer platforms to streamline software delivery.
  • • Document technical approaches, system designs, and implementation guidelines for knowledge transfer and long-term team enablement.
  • • Apply deep understanding of transformer architectures and large language models to evaluate and select appropriate models for specific engineering use cases.
  • • Ensure security, scalability, and performance are integrated into all AI-assisted engineering solutions.
  • • Participate in technical interviews and evaluations as part of GT’s client delivery process.

🎯 Requirements

  • • Strong background in software engineering, full-stack development, backend engineering, or software architecture
  • • Strong hands-on Python experience
  • • Experience with microservice API development (REST, GraphQL, or gRPC)
  • • Practical experience with AI-assisted development tools (Claude Code, Cursor, Codex, GitHub Copilot)
  • • Hands-on experience with LLM applications, RAG pipelines, AI agents, or model routing
  • • Deep understanding of large language models and transformer architectures

🏖️ Benefits

  • • Short-term consulting engagement with flexible, remote work structure
  • • Direct exposure to a leading global consulting firm and a US-based enterprise client
  • • Opportunity to work on cutting-edge AI engineering projects at the forefront of developer productivity
  • • Client-facing role with high impact on engineering transformation initiatives

Skills & Technologies

Python
FastAPI
PostgreSQL
MongoDB
AWS
Data Science
Senior
Remote
Degree Required

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About GT (Global Talent) Ltd

GT operates as a tech staffing and engineering hub provider that helps high‑growth companies build and manage remote development teams and delivery centers—handling recruitment, local operations, payroll/EOR, and ongoing management to scale engineering capacity in CEE and other regions.

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