Time since we first saw it
Day 32
Similar jobs usually come down between day 4 and day 77.
At Devoteam, jobs usually come down by about day 22.
From 51 similar postings that came down, and 152 of Devoteam’s. Coming down is not always a hire.
Reads like an AI Engineer role: building products on existing AI models.
Lisboa, Lisboa, Portugal
Live, first seen by us 32 days agoWork setup in the employer’s posting: On-siteFrom the employer’s posting
Employment type in the employer’s posting: Full-timeFrom the employer’s posting
Design, develop and deploy end-to-end AI pipelines using LLMs and foundation models
Turn AI prototypes and experimental agents into scalable production systems
Monitor AI applications for output quality, hallucinations and performance
Build data pipelines for vector databases and optimize context retrieval for RAG
Design, develop, and deploy end-to-end AI pipelines, focusing on integrating Large Language Models (LLMs) and Foundation Models into production environments
transition AI prototypes and experimental agents into scalable, production-grade systems
Implement advanced monitoring for AI applications, focusing on output quality, hallucination detection, and performance tracking
Collaborate with Data Engineers to build efficient data pipelines for vector databases (Chroma, Pinecone, Weaviate) and optimize context retrieval for RAG
3+ years as an AI Engineer, ML Developer, or Software Engineer with a focus on AI integration.
Strong proficiency in Python (clean, production-ready code) and experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex).
Practical experience with Generative AI, Prompt Engineering, and fine-tuning Foundation Models (OpenAI, Hugging Face, Anthropic).
Knowledge of Vector DBs (e.g., Pinecone, Weaviate, Chroma) and proficiency in SQL for data handling.
Experience deploying AI applications on Cloud platforms (Azure AI, Vertex AI, or AWS Bedrock) and managing the AI lifecycle (LLMOps).
Familiarity with Docker and API development (FastAPI/Flask) to build scalable AI services.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.
Day 32
Similar jobs usually come down between day 4 and day 77.
At Devoteam, jobs usually come down by about day 22.
From 51 similar postings that came down, and 152 of Devoteam’s. Coming down is not always a hire.
44 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Work closely with stakeholders to transition AI prototypes and experimental agents into scalable, production-grade systems, implementing modern LLM Ops practices. - Develop robust, efficient code using Python and frameworks such as LangChain, LlamaIndex, or AutoGPT, alongside traditional libraries like PyTorch or TensorFlow when needed. - Implement advanced monitoring for AI applications, focusing on output quality, hallucination detection, and performance tracking (e.g., using RAGas or Arize Phoenix).
- 3+ years as an AI Engineer, ML Developer, or Software Engineer with a focus on AI integration. - Strong proficiency in Python (clean, production-ready code) and experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex). - Practical experience with Generative AI, Prompt Engineering, and fine-tuning Foundation Models (OpenAI, Hugging Face, Anthropic).
- Practical experience with Generative AI, Prompt Engineering, and fine-tuning Foundation Models (OpenAI, Hugging Face, Anthropic). - Knowledge of Vector DBs (e.g., Pinecone, Weaviate, Chroma) and proficiency in SQL for data handling. - Experience deploying AI applications on Cloud platforms (Azure AI, Vertex AI, or AWS Bedrock) and managing the AI lifecycle (LLMOps).
- Knowledge of Vector DBs (e.g., Pinecone, Weaviate, Chroma) and proficiency in SQL for data handling. - Experience deploying AI applications on Cloud platforms (Azure AI, Vertex AI, or AWS Bedrock) and managing the AI lifecycle (LLMOps). - Familiarity with Docker and API development (FastAPI/Flask) to build scalable AI services.
- Experience deploying AI applications on Cloud platforms (Azure AI, Vertex AI, or AWS Bedrock) and managing the AI lifecycle (LLMOps). - Familiarity with Docker and API development (FastAPI/Flask) to build scalable AI services. - Ability to translate business needs into AI solutions and communicate technical logic to non-tech teams.
- Strong proficiency in Python (clean, production-ready code) and experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex). - Practical experience with Generative AI, Prompt Engineering, and fine-tuning Foundation Models (OpenAI, Hugging Face, Anthropic). - Knowledge of Vector DBs (e.g., Pinecone, Weaviate, Chroma) and proficiency in SQL for data handling.
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New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under AI Engineer, by the work the posting describes.
AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.
Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.
An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.
We are seeking a versatile and passionate AI to join our data science and engineering team. You will be instrumental in bridging the gap between data science research and production-ready applications, building scalable machine learning systems that drive business value. This role requires a strong balance of software engineering principles and ML expertise.
Key Responsibilities
Design, develop, and deploy end-to-end AI pipelines, focusing on integrating Large Language Models (LLMs) and Foundation Models into production environments.
Work closely with stakeholders to transition AI prototypes and experimental agents into scalable, production-grade systems, implementing modern LLM Ops practices.
Develop robust, efficient code using Python and frameworks such as LangChain, LlamaIndex, or AutoGPT, alongside traditional libraries like PyTorch or TensorFlow when needed.
Implement advanced monitoring for AI applications, focusing on output quality, hallucination detection, and performance tracking (e.g., using RAGas or Arize Phoenix).
Collaborate with Data Engineers to build efficient data pipelines for vector databases (Chroma, Pinecone, Weaviate) and optimize context retrieval for RAG.
Stay at the forefront of the rapidly evolving Generative AI landscape, exploring new techniques in prompt engineering, fine-tuning, and agentic workflows.
3+ years as an AI Engineer, ML Developer, or Software Engineer with a focus on AI integration.
Strong proficiency in Python (clean, production-ready code) and experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex).
Practical experience with Generative AI, Prompt Engineering, and fine-tuning Foundation Models (OpenAI, Hugging Face, Anthropic).
Knowledge of Vector DBs (e.g., Pinecone, Weaviate, Chroma) and proficiency in SQL for data handling.
Experience deploying AI applications on Cloud platforms (Azure AI, Vertex AI, or AWS Bedrock) and managing the AI lifecycle (LLMOps).
Familiarity with Docker and API development (FastAPI/Flask) to build scalable AI services.
Ability to translate business needs into AI solutions and communicate technical logic to non-tech teams.
Degree in Computer Science, Engineering, or a related quantitative field.
Professional level of English (written and spoken).
The Devoteam Group works for equal opportunities, promoting its employees based on merit and actively fights against all forms of discrimination. We are convinced that diversity contributes to the creativity, dynamism and excellence of our organization. All of our vacancies are open to people with disabilities.
At Devoteam, we believe that technology with strong human values can actively drive change for the better. Discover how Tech for People unlocks the future, creating a positive impact on the people and the world around us. We are a global leading player in Digital Transformation for leading organisations across EMEA, with a revenue of €1B. We believe in transforming technology to create value for our clients, partners and employees in a world where technology is developed for people. We are proud of the culture we have built together. We are proud of our people at the service of technology. We are proud of our diverse environment. Because we are #TechforPeople. Join our multidisciplinary team of Cloud experts, Designers, Business consultants, Security experts, Engineers, Developers and other extraordinary talents, spread across more than 20 EMEA countries. Become one of our +10.000 tech and business leaders on cloud, data and cyber security. Let’s fuse creativity with technology together and build innovative solutions that actively change things for the better.
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Lisboa, Lisboa, Portugal
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