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Tech Stack
Tools & technologiesAWSAzureCloudGoogle Cloud PlatformJavaJavaScriptPythonTypeScript.NET
About the role
Key responsibilities & impact- Lead technical discovery with clients to understand their systems, data, workflows, security requirements, and technical challenges
- Translate business needs and approved architectures into clear technical plans, implementation priorities, and deployment activities
- Develop and integrate production-ready solutions using APIs, enterprise applications, cloud services, data platforms, and AI technologies
- Collaborate with AI Engineers, Software Engineers, Data Engineers, and Architects to coordinate technical implementation and resolve integration challenges
- Own technical deployment and rollout within the agreed scope, ensuring solutions operate reliably in client environments
- Work closely with client teams during implementation, resolve technical issues, support adoption, and enable users to operate deployed solutions
- Track technical delivery progress, production performance, costs, and measurable outcomes while documenting solutions and reusable engineering practices
Requirements
What you’ll need- Strong hands-on experience developing, integrating, and deploying production software, AI, data, or cloud solutions
- Experience writing, debugging, and maintaining production-quality code
- Experience integrating enterprise applications, APIs, data sources, authentication systems, and cloud services
- Proven ability to translate technical requirements into implementation plans and production deployments
- Experience working directly with clients or business stakeholders while maintaining technical ownership
- Strong communication skills, including the ability to explain technical decisions, risks, and implementation challenges to technical and non-technical audiences
- Strong programming skills in at least one relevant language, such as Python, TypeScript/JavaScript, Java, or C#/.NET
- Experience with REST APIs, webhooks, enterprise integrations, and backend services
- Hands-on experience with at least one major cloud ecosystem, such as AWS, Azure, or GCP
- Understanding of software engineering practices, including Git, testing, CI/CD, containers, and production monitoring
- Familiarity with AI/GenAI technologies, including LLM APIs, RAG, AI agents, and AI-enabled workflows
- Knowledge of application security, authentication, identity management, and production deployment practices
- Advanced experience building GenAI applications, RAG systems, or agentic workflows
- Experience with frameworks and tools such as LangGraph, MCP, OpenAI, Anthropic, or comparable technologies
- Background in backend, full-stack, data, or cloud/platform engineering
- Experience designing solutions for complex enterprise or regulated environments
- Consulting or professional services experience with multiple clients
- Experience in Forward Deployed Engineering, Customer Engineering, or other client-embedded technical roles
Benefits
Comp & perks- International and multicultural projects
- Opportunities to work with leading technologies in Data, Cloud, and AI ecosystems
- Access to training programs and continuous professional development
- Professional growth opportunities and internal mobility
- A culture built on collaboration, innovation, and continuous learning