Jobs at Ciklum

Conduct outbound cold calls, email, and LinkedIn campaigns to North American prospects. Pitch consulting and digital engineering services, engage decision-makers, qualify opportunities, schedule calls, follow up with interested prospects, coordinate pre-sales discussions with technical teams, and document activities in Salesforce. The role requires international inside sales experience, strong English communication, online research skills, and the ability to work in a high-volume environment.

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.

Design and implement an end-to-end QA automation framework for Microsoft Fabric data platforms. Validate Medallion Architecture layers, pipelines, schemas, data quality, reconciliations, Power BI semantic models, reports, and AI agents. Build regression suites using SQL, Python, PySpark, Playwright, and TypeScript; investigate root causes; monitor observability metrics; configure alerts; and integrate automated checks into Azure DevOps or other CI/CD systems. Collaborate with data engineering, BI, AI, and DevOps teams.

Designs and maintains scalable Playwright and TypeScript automation for responsive, data-intensive web applications. Covers functional, integration, contract, end-to-end, reliability, security, accessibility, performance, and cross-browser testing. The role validates complex UI behavior, large datasets, rendering, network performance, and responsiveness while diagnosing issues through developer tools and telemetry. It also promotes quality across the development lifecycle and uses AI-assisted tools to improve test design and maintenance.

Design and develop scalable automated tests for server-side applications, REST APIs, microservices, integrations, asynchronous workflows, and Azure-based systems. Build functional, integration, contract, end-to-end, reliability, and API security coverage using Playwright with TypeScript or C#. Integrate quality gates into CI/CD and Docker deployments, validate data contracts and event-driven workflows, and collaborate with developers to shift quality left. Use AI-assisted tools to improve test design, debugging, and refactoring.

Design and deploy enterprise GenAI and agentic workflow platforms for pharmaceutical and life sciences applications. Build multi-agent systems, RAG pipelines, AWS Bedrock integrations, governed AI workflows, Python/FastAPI microservices, React applications, databases, and cloud infrastructure. Implement security, compliance, auditability, automated testing, and production deployment across healthcare-focused systems.

Architects and deploys production-grade agentic AI and multi-agent systems using LLMs, RAG, vector databases, prompt engineering, and NLP. Designs autonomous workflows, tool calling, memory, routing, evaluation, observability, and guardrails. Builds backend APIs and microservices while implementing testing for model drift, prompt regression, and agent reliability. Requires advanced Python, hands-on production Generative AI experience, and expertise with agent orchestration frameworks and vector search.

Lead DevOps Engineer responsible for building AWS development, testing, and production environments; creating CI/CD pipelines; managing infrastructure as code, secrets, IAM, networking, API gateways, observability, monitoring, and alerting. The role also develops runbooks, rollback plans, deployment documentation, and operational handover materials while supporting production releases under enterprise change-control and cloud-governance processes.

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.

Develop and maintain Oracle APEX applications, Oracle Analytics Server/OBIEE reporting solutions, BI Publisher reports, and Oracle database objects. Build dashboards, workflows, integrations, REST APIs, and data models; write complex SQL and PL/SQL; troubleshoot and tune application and database performance; support deployments, testing, production issues, documentation, and stakeholder collaboration.

Design, build, and scale production AI agent workflows using AWS Bedrock AgentCore, Step Functions, Claude, MCP, RAG, and guardrails. Develop Python/FastAPI backends, agent-facing interfaces, document-processing pipelines, enterprise integrations, and AWS infrastructure. Implement observability, evaluations, security controls, human approval workflows, and CI/CD. Work directly with enterprise customers and nontechnical stakeholders to deliver end-to-end AI solutions with minimal guidance.

Owns end-to-end automated quality engineering for an AI agent development platform. Responsibilities include frontend and backend automation, Temporal workflow reliability testing, multi-tenant isolation, sandbox and security testing, statistical LLM evaluation, adversarial test corpora, HITL validation, performance and concurrency testing, observability assertions, CI/CD release gates, evidence reporting, synthetic data pipelines, and mentoring QA engineers.

Develop, customize, integrate, test, deploy, and support Dynamics 365 Business Central solutions using AL and extensions. Collaborate with cross-functional teams to translate business requirements into technical designs, integrate third-party systems through APIs and web services, document solutions, maintain coding standards, support upgrades, tune performance, and diagnose operational issues. The role also involves Power Platform capabilities, reporting, database work, CI/CD tools, and specialized Business Central workflow and finance integrations.

Lead a 10–15-person engineering team building agentic AI systems from the ground up. Set architecture strategy for planning, memory, tool use, multi-agent coordination, guardrails, observability, evaluations, reliability, and safety. Drive adoption of an AI-Driven Development Lifecycle, partner with product managers on ambiguous requirements, oversee delivery and technical reviews, and support hiring, mentorship, career growth, and leadership reporting.

Gather and document business and functional requirements for card and payment solutions. Collaborate with stakeholders, product owners, engineering, QA, and processors across the SDLC. Define user stories, process flows, acceptance criteria, and technical specifications; analyze impacts and dependencies; support UAT, integration testing, defect triage, releases, and production issues. Apply expertise in card processing, payment networks, ISO 8583, tokenization, digital wallets, chargebacks, reconciliation, and regulatory compliance.

Lead and execute firmware development for embedded devices from requirements to production. Design, code, test, debug, and optimize system software; interface with hardware; integrate and validate new products; support QA and post-production; assess third-party/open-source software; apply embedded design best practices; research and prototype proofs of concept; mentor junior engineers.

A referral submission form inviting people to share a friend's details and CV for future job matches. The employer will contact referred candidates when a suitable opportunity arises; applicants are asked to follow referral rules and guidelines.

Lead architecture for enterprise AI initiatives across products, platforms, and shared capabilities. Define AI architecture standards, reference patterns, governance, security, and operational guardrails. Guide solutions involving LLM applications, retrieval systems, agentic workflows, orchestration, evaluation, observability, and cloud-native platforms. Partner with business, product, and engineering leaders, influence strategic decisions, mentor technical teams, and support AI-enabled software development and platform modernization.

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.

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).