Jobs at Ciklum

Lead design, development, and deployment of production-grade LLM and RAG-based AI solutions. Improve retrieval performance, build automated evaluation and validation frameworks, instrument pgvector retrieval KPIs, integrate metrics into CI/CD, and mentor mid-level engineers while driving technical reviews and best practices.

Lead and scale Retail & Consumer Goods consulting: drive discovery workshops, presales solutioning, strategic client advisory, author domain IP, and win large digital transformation deals across e-commerce, merchandising, and digital experience.

Manage end-to-end resource allocation and deployment, optimize bench utilization, forecast demand and build talent supply plans, drive internal mobility, partner with TA for external hires, and track utilization and deployment metrics.

Design and implement backend functionality, participate in architecture and code reviews, collaborate with stakeholders, improve solutions and processes, deliver roadmap items, provide field support, and produce testable, performant code across the SDLC.

Own platform-wide quality assurance for an AI-powered multilingual knowledge platform. Define test strategies and acceptance criteria, test retrieval accuracy and relevance, validate German, Italian, French, and Dutch outputs, verify API contracts and NICE synchronization, manage regression coverage, and integrate QA processes into CI/CD pipelines. Evaluate RAG/LLM outputs and collaborate with business analysts, developers, and technical leads to ensure consistent quality across systems.

Lead design and maintain a secure, production AWS environment for an Agent Development Platform. Implement Firecracker MicroVMs or container isolation, provision and scale vector and graph databases, build event-driven streams, automate infrastructure with IaC and CI/CD, integrate identity for multi-tenancy, and enforce strict egress controls to prevent data exfiltration.

Lead design, build, and scale production-grade Generative AI applications using LLMs, RAG, LangChain, vector databases, and agentic systems. Own AI orchestration, containerized Kubernetes deployments, CI/CD, data ingestion from enterprise sources, monitoring for high uptime, and governance/compliance to deliver measurable business impact and reusable AI accelerators.

Lead and execute end-to-end embedded firmware development for devices—from requirements through production and post-production support. Design, implement, test, debug, and optimize system software and I/O, interface with hardware, validate new product designs, assess third-party/open-source software, support QA, perform research and prototypes, and mentor junior teammates.

Backend-focused Senior .NET Engineer responsible for building new functionality, contributing to architecture and code reviews, collaborating with stakeholders, ensuring high coding and test standards, improving solutions and processes, supporting field issues, and using AI tools to accelerate development.

Lead design and delivery of scalable Python backend and AI platforms. Architect microservices, integrate LLMs and vector retrieval, build AI workflows, optimize data pipelines with Databricks and SQL, lead cloud deployments on Azure/AWS, mentor engineering teams, and collaborate with product and data science to productionize Generative and Agentic AI solutions.

Design and develop embedded firmware for battery-powered IoT devices using C/C++ and assembly. Implement wireless protocols, RTOS applications, secure boot and encryption, optimize power and performance, collaborate with hardware, cloud and mobile teams, and build testing and debugging frameworks.

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Design, build, and maintain high-performance backend systems and scalable APIs using Python and FastAPI. Integrate AI-driven solutions (Generative/Agentic AI), work with Databricks and SQL/RDBMS, collaborate with cross-functional teams, optimize performance, and contribute to architecture and technical decisions.

Operate the deal desk and manage opportunity-to-booking lifecycle in Salesforce and DealHub. Ensure booking accuracy, support contracting workflows, coordinate across Sales/Finance/Legal, maintain renewal pipeline, and provide peak-period closing support (EOM/EOQ/EOY).

Design, build, and deliver enterprise-grade Generative AI and AI/ML platform capabilities: reusable services, APIs, microservices, RAG and agentic solutions, model lifecycle tooling, inference and monitoring, event-driven streaming with Kafka, CI/CD and DevOps automation, and platform observability to accelerate AI adoption across business domains.

Lead quality engineering for a cloud-native data platform by building and maintaining end-to-end automation frameworks for backend (.NET/Azure Functions) and frontend (Angular), validate execution engines, automate data/pipeline verification on Snowflake, integrate tests into Azure DevOps CI/CD, and define test strategies including performance/load testing.

Lead architecture and engineering of enterprise-scale Generative AI and data platforms. Design reusable platform services for end-to-end AI/ML lifecycle, build agentic applications and event-driven systems, enforce CI/CD and DevSecOps, ensure security/governance/observability, mentor engineers, and drive platform modernization using cloud-native, containerized, and distributed technologies.

Lead platform automation for enterprise Generative AI and data platforms: design and build IaC, CI/CD, observability, deployment automation, and self-service capabilities to accelerate AI/ML lifecycle, reliability, governance, and developer productivity across cloud-native distributed environments.

Lead end-to-end design, build, deployment and iteration of AI-agent solutions. Embed with clients to map workflows, architect multi-agent systems, integrate enterprise systems and RAG pipelines, implement guardrails and observability, and liaise with non-technical stakeholders to drive adoption.

Build and enhance enterprise data pipelines into Databricks Unity Catalog and Delta Lake. Improve remediation and entity-matching layers (including D&B DataBlocks), integrate APIs, and support LLM-assisted remediation and CMG redesign projects.