Pagrindinis
AI Engineer
Timi?oara, Timi?Oara, ROM, Romania
Įmonė:
Xerox
Klientas / Darbdavys:
IBM
Paskelbta: 23.05.2026
Galutinė data: 07.07.2026
Darbo nuoroda: 82570e5eabd88ff7703a743c3efc8771
Informacija apie darbą
Vieta
Timi?oara, Timi?Oara, ROM, Romania
Įmonė
Xerox
Klientas / Darbdavys
IBM
Darbo nuoroda
82570e5eabd88ff7703a743c3efc8771
Skelbimo tipas
Pagrindinis
Reikalingas ES darbo leidimas
Ne
Paskelbta
23.05.2026
Galutinė data
07.07.2026
Darbo aprašymas
**Introduction** A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences. **Your role and responsibilities** As an AI Engineer, you will be responsible for building and deploying AI-powered systems, including RAG pipelines and agentic systems. You will design and implement backend services using Python and FastAPI, and integrate with various tools and systems. You will also deploy and operate services on AWS, ensuring scalability and reliability. **Required technical and professional expertise** * Experience building RAG pipelines and agentic systems * Strong understanding of LLM orchestration frameworks (e.g. LangChain, LangGraph, Langfuse) * Strong backend engineering experience with Python * Hands-on experience building APIs/services with FastAPI * Experience integrating with MCP tools, internal APIs, and enterprise systems **Preferred technical and professional experience** * Expertise with OpenSearch (index design, ingestion pipelines, analyzers, relevance tuning) * Knowledge of embeddings generation and vector database best practices * Experience with OpenSearch plugins, custom scoring, or ingestion frameworks * Familiarity with Kubernetes * Experience with observability stacks (OpenTelemetry, Prometheus, Grafana, Langfuse) IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.
Įgūdžiai
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