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AI Engineer (Coimbra)

Full Stack LLM Development Senior Analyst | Early Career | Full time
Job No. R00331828 | Coimbra
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Accenture Technology powers our clients to achieve high performance. We combine business and industry insights with innovative technology to drive growth for your business. We extend our technology and business capabilities through a powerful alliance ecosystem of market leaders and innovators to provide our clients the best specialized skills and tailored solutions.

We are seeking a highly qualified professional to join our team as an AI / Forward Deployed Engineer (multiple seniority levels). This role supports an Accenture client context, working on a global-market AI product already deployed across multiple geographies. You will work close to customers, product, engineering, architecture, and delivery teams to translate business needs into robust solutions through configuration, integration, adaptation, and continuous improvement. We are hiring profiles with 1 to 6 years of experience (from early-career to senior contributors who can guide others).

Qualifications

  • 2–6 years of experience in technology projects (application development, implementation, systems integration, or client-facing delivery)

  • Degree in Computer Engineering, Electrical Engineering, Telecommunications, Data Science, or similar field (or equivalent practical experience)

  • Experience or exposure to AI-enabled platforms, digital solution implementation, or automation projects

  • Solid understanding of APIs and system integration, including REST, common integration patterns, and enterprise workflows

  • Practical programming skills in Python and/or JavaScript/TypeScript

  • Ability to understand business requirements and translate them into technical solutions

  • Strong analytical, problem-solving, and communication skills; comfortable collaborating with cross-functional and multicultural teams

  • Interest in and/or experience with Generative AI, including LLMs, and AI-enabled components (automation, agents)

Responsibilities

  • Understand the product’s capabilities, limitations, configuration options, and extension points

  • Analyze functional and technical requirements with customer and delivery teams and translate them into implementable solutions

  • Configure, adapt, and implement AI-enabled solutions aligned to specific customer use cases

  • Design and support integrations between the platform and enterprise systems using APIs, authentication/authorization, and secure integration practices

  • Participate in technical solution design to ensure alignment with customer architecture and operational constraints

  • Implement and support flows, automations, agentic components, tool calling/function calling, and other AI-enabled platform features

  • Test, validate, debug, and optimize solutions to meet quality, reliability, and performance requirements

  • Apply AI knowledge (where applicable) including LLM, Speech-to-Text (STT), and Text-to-Speech (TTS) capabilities to support customer needs

  • Contribute to reusable assets, implementation patterns, best practices, and technical documentation

  • Identify opportunities to improve platform usage and consistency across multiple geographies/markets

  • For more senior profiles (typically 3–6 years): lead or co-lead use case analysis, assess trade-offs (latency/quality/cost/scalability), identify risks and mitigations, and support junior engineers in problem-solving

Nice to Have

  • Familiarity with different market LLMs/providers, their strengths/limitations, and evaluation approaches

  • Knowledge of prompting techniques, prompt testing, and prompt evaluation methods

  • Exposure to agentic frameworks, multi-agent patterns, MCP/tool-use concepts, or orchestration approaches

  • Experience with SaaS platforms, cloud environments, or enterprise architectures

  • Exposure to observability/logging/debugging tools and troubleshooting in production-like environments

  • Experience working on client-facing initiatives or in international/multi-geography contexts

  • Familiarity with STT/TTS considerations (quality, latency, language support, multilingual requirements)

Additional Information

  • Location: Coimbra

  • Working Model: Hybrid

Coimbra

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