أساسي
AI Engineer
تم النشر: 18.05.2026
تاريخ الإغلاق: 02.07.2026
مرجع وظيفي: c56ab6f546aa97c6a82bf44c7427b137
معلومات الوظائف
الموقع
Lisboa, Lisbon Metropolitan Area, Portugal
الشركة
Jobio
العميل / صاحب العمل
Mesh-ai
مرجع وظيفي
c56ab6f546aa97c6a82bf44c7427b137
نوع القائمة
أساسي
مطلوب تصريح عمل من الاتحاد الأوروبي
لا
تم النشر
18.05.2026
تاريخ الإغلاق
02.07.2026
وصف الوظيفة
About Mesh-AIWe’re a transformation consultancy and we exist to reimagine how enterprises operate, making data and AI their competitive advantage. We turn enterprises into data-driven and AI enabled organisations, unleashing business growth and accelerating outcomes.We're proud to be partnered with leading innovators like Anthropic, OpenAI, and AWS and are growing our AI Engineering team to design and deliver production-grade AI systems that redefine how enterprises create value.We’re building an open, collaborative culture and we are always on the lookout for top talent to join us in our next phase of growth. If you’re interested in working on business-defining engagements with some of the brightest minds in the industry, apply below!OverviewWe're seeking an experienced AI Engineer to design, build, and deploy production-grade AI systems powered by large language models. This role sits at the intersection of software engineering and AI implementation, focusing on building reliable, scalable applications rather than model training or research.You'll work with cutting-edge LLM technologies, building advanced AI systems that solve complex real-world problems through multi-agent orchestration, intelligent tool integration, and robust production workflows.You'll be crafting the orchestration layer that makes these systems production-ready—handling failure modes, optimizing agent collaboration, and ensuring consistent, reliable outputs at scale.You’ll combine strong software engineering fundamentals with deep practical knowledge of LLM capabilities, limitations, and best practices for building non-deterministic systems that users can trust.ResponsibilitiesDesign and implement production AI systems integrating LLMs, RAG pipelines, vector databases, and agentic frameworks.Create evaluation frameworks to measure and monitor system performance, accuracy, and reliability.Build and maintain production-grade AI applications with clean code, appropriate error handling, APIs, and data pipelines.Experience implementing, maintaining and evaluating retrieval systems (vector/graph databases, ingestion pipelines, chunking strategies, retrieval techniques such as HyDE).Implement feedback loops and observability to continuously improve system performance.Craft effective prompts and optimize for latency, cost, and quality across different model providers and configurations.Required Skills and ExperienceHands-on experience building applications with LLM APIs and deep understanding of their capabilities, limitations, and failure modes.Practical implementation of RAG architectures, vector databases, knowledge graphs and prompt engineering.Experience building multi-step LLM workflows and agentic systems using frameworks (e.g. SDK, Strands, Claude Agents SDK, LangGraph, etc.) or custom implementations where needed.Strong Python (or other modern programming language) proficiency with production API/service development experience and cloud platform knowledge (AWS, GCP, Azure).Understanding of distributed systems, CI/CD, testing frameworks, and deployment pipelines.Solid foundations and understanding of production-grade, cloud-native platform and infrastructure requirements, design, and implementation.Strong data manipulation skills (pandas, SQL) and understanding of evaluation strategies for LLM-based systems.Ability to work with ambiguity and optimise non-deterministic systems through a process of experimentation and evaluation while balancing latency/cost/quality tradeoffs.Nice to HavesExperience with AI-assisted coding using tools like Claude Code, OpenAI Codex, Github Copilot.Experience with fine-tuning LLMs for domain-specific applications and knowledge of when fine-tuning is preferable to prompt engineering or RAG.Experience with real-time streaming, multimodal models, or search technologies like Elasticsearch.Familiarity with model observability tools (LangSmith, Weights & Biases) and cost optimization strategies.Experience in specialized verticals (financial services, energy, healthcare, legal, retail) with understanding of compliance, security, and responsible AI practices.Experience with setting up tool calling agents, handoffs, and guardrails.Why Mesh-AIFast-growing start-up organisation with huge opportunity for career growth.Highly competitive salary package along with company bonus.A hugely collaborative working environment where every person’s viewpoint is considered - a chance to make your mark on the business from day one!Financially backed business meaning security and support for new initiatives and global market expansion.Pick your own Gear! Macbooks, PCs, Accessories!Drive your development with a personal learning budget. Want to know more? Get in touch with ******** . Otherwise apply here.
المهارات
Agile Project Management
Algorithms
analyse big data
analyse business requirements
apply ICT systems theory
apply systemic design thinking
Artificial Neural Networks
Assembly (computer programming)
assess ICT knowledge
build business relationships
build predictive models
build recommender systems
Business Analytics
Business Intelligence
business process modelling
C
COBOL
CoffeeScript
Common Lisp
computer programming
Computer Simulation
Computer Vision
create data sets
creatively use digital technologies
Data Mining
Data Models
Data Science
database development tools
Deep Learning
define technical requirements
deliver visual presentation of data
design application interfaces
design database scheme
design process
develop creative ideas
develop statistical software
digital data processing
Erlang
Groovy
Haskell
ICT project management methodologies
identify processes for re-engineering
Information Architecture
information categorisation
Information Extraction
information structure
Java (computer programming)
JavaScript
lean project management
LINQ
Lisp
manage business knowledge
manage ICT data classification
manage ICT semantic integration
Matlab
Microsoft Visual C++
ML (computer programming)
N1QL
Objective-C
OpenEdge Advanced Business Language
operational research
Pascal (computer programming)
perform dimensionality reduction
Perl
PHP
principles of artificial intelligence
Process-based management
Prolog (computer programming)
Python (computer programming)
R
resource description framework query language
Ruby (computer programming)
SAP R3
SAS language
Scala
Scratch (computer programming)
Smalltalk (computer programming)
SPARQL
Swift (computer programming)
systems development life-cycle
task algorithmisation
TypeScript
Unstructured Data
use data processing techniques
utilise machine learning
VBScript
Visual Basic
visual presentation techniques