Python developer állások XVI. kerületben (ai és automatizáció)

• Design and own the Azure Native Data & AI Platform architecture
• Lead Azure Databricks platform implementation and evolution
• Define enterprise data, analytics, ML and AI platform standards and best practices
• Design Lakehouse and Medallion architectures

Developing and executing a comprehensive vulnerability management program, encompassing regular scanning, penetration testing coordination, risk assessment, prioritization, and remediation tracking across all environments...

• Megtervezed és a csapattal közösen felépíted az agentic AI-platformot, amelyre a fejlesztési munkafolyamatainkat alapozzuk.
• Coding agenteket és AI-toolchaineket integrálsz a meglévő C#/.NET és Vue.js ökoszisztémánkba, kialakítva az önálló és többagentű működés feltételeit.

• Building tools and automation that help Wise's FinCrime teams develop and improve machine learning models
• Working on model experimentation, bias and fairness, automated training-set maintenance, and threshold analysis

• Deploying and scaling EcliptOS platform in real-world environments and ensuring it works at scale
• Owning the EcliptOS platform delivery lifecycle, bridging product engineering and client environments

• Designing and building agentic systems that plan, call tools and automate real business workflows
• Designing and building multi-agent (agent-to-agent) solutions in which agents hand work to each other, review it and escalate to a human when needed

• Üzleti probléma és megoldás teljes körű megértése, BRS véleményezése, jóváhagyása
• IT megoldás magas- és mélyszintű tervezése (funkcionális és architektúrális)
• Rendszer szintű SRS dokumentációk készítése, véleményezése – különös figyelemmel az interfészekre (adatfolyamok, adatmapping)

• Designing, developing, and deploying robust and scalable IAM services, including authentication, authorization, user provisioning, and directory services
• Leading technical discussions, conducting architectural reviews, and providing mentorship to junior and mid-level engineers on the team

• Being involved in the design process of a SoC by integrating the latest Arm IP products while ensuring correct functional behaviour
• Developing RTL code using System Verilog
• Running EDA tools to check the design and analyze results
• Using AI-assisted engineering tools to support development and debug

• Producing high quality code for the full technological stack, from database to UI and everything in between
• Assisting with troubleshooting basic issues and improving application performance by responding to specific problems and fixing defects

• Leading architecture design
• Driving technology decisions
• Co-creating innovative products
• Mentoring clients to adopt Agile practices and engineering excellence
• Leading project workstreams
• Driving architectural decisions
• Building scalable solutions using Agile methodologies

Taking ownership of delivering agentic solutions across multiple client deployments, guiding them from initial prototypes and onboarding through to stable adoption and scaled use...

• Designing and implementing data fabric architecture across heterogeneous data sources and platforms
• Developing scalable ETL/ELT pipelines for batch and real-time data integration
• Integrating structured and unstructured data from databases, APIs, SaaS applications, data lakes, and enterprise systems

• Assisting in integrating data from various sources (e.g. APIs, databases, files) into centralized data platforms
• Ensuring the quality and availability of data across data pipelines and storage systems
• Supporting the implementation of data models and data warehouse solutions

• Working closely with customers to analyze business needs and translate them into technical requirements
• Participating in pre-sales discussions, helping shape tailored technical solutions
• Collaborating with Sales and Customer Success teams to ensure smooth project execution and client satisfaction

Driving modeling and experimentation for SEON's fuzzy matching and AML screening quality, turning ambiguous problems into well-defined approaches and carrying them from experiment through release and operation...

• Designing and building artificial intelligence and machine learning solutions for enterprise clients
• Operationalizing artificial intelligence and machine learning solutions, combining custom models with cloud and third-party AI services to deliver production-ready outcomes

• Design, build and deploy AI agents and multi-agent pipelines for B2B clients across sales, support, and operations
• Architect integrations between LLM layers, voice AI (VoIP/SIP), CRMs, and business workflows

Designing and building learner models, including knowledge tracing and longitudinal approaches, that power mastery and progression features surfaced to learners and educators...

• Owning the data models and storage architecture behind AI systems, across relational, graph, and retrieval-oriented data
• Building and operating the APIs, backend services, and pipelines that keep data current and accessible