Data engineer in AI applications

At Synechron, we harness the power of digital transformation to drive business success. As a global consulting firm, we combine creativity with advanced technology to deliver innovative solutions across industries. Recognized with multiple employer awards, we are committed to building talented teams and creating a dynamic work environment.

• Design, develop, and maintain Python-based data and AI applications, including REST APIs using FastAPI.
• Build and optimize LLM applications, RAG pipelines, semantic search solutions, and AI agents using LangChain and LangGraph.
• Integrate Azure OpenAI and OpenAI APIs, working with GPT-4 and GPT-5 models, embeddings, vector databases, and Azure data services.
• Develop efficient SQL and NoSQL queries and work with Azure Blob Storage and Azure Databases.
• Evaluate, test, troubleshoot, deploy, and monitor AI models and applications to ensure quality, reliability, and performance.
• Collaborate with engineering and product teams and contribute to clean code, Git/GitHub workflows, CI/CD, and technical documentation.

• 5–8 years of professional experience in data engineering, software engineering, or a related role.
• Strong Python development skills and hands-on experience with FastAPI and REST API development.
• Strong SQL and NoSQL query writing skills.
• Hands-on experience with Azure OpenAI, OpenAI APIs, Generative AI, and GPT-4/GPT-5.
• Experience building LLM applications, RAG pipelines, AI agents, and agentic AI solutions.
• Practical experience with LangChain, LangGraph, vector databases, embeddings, vector search, and semantic search.
• Experience with Azure Blob Storage, Azure Databases, Git, and GitHub.
• Experience with AI model evaluation, testing, troubleshooting, deployment, monitoring, and observability.
• One of the prerequisites for this position is that the prospective candidate must possess a valid work permit for Serbia.
• Будет плюсом: Experience with Flask or Django, Knowledge Graphs, Ontology concepts, and Semantic Layers; Exposure to MLOps and LLMOps practices and frameworks; Knowledge of Elasticsearch, Kafka, and Redis; Experience with Docker, Kubernetes, CI/CD pipelines, Azure DevOps, or GitHub Actions; Exposure to AWS or GCP cloud services; Experience developing conversational AI or Copilot solutions

• Compensation package based on experience and skills
• Flexible hours and hybrid work options, allowing you to achieve a work-life balance that suits your needs
• Private health insurance plan
• Access to continuous training, accredited certifications, access to unlimited Udemy courses and a range of resources to help you grow professionally
• Personalized leadership training program
• FitPass membership to support your well-being and mental health support programs
• Comprehensive Referral Rewards Program