AI Engineer (Forward Deployed)

About the Role
We are seeking a Forward Deployed Engineer (AI Services) responsible for the end-to-end delivery of AI solutions on cloud AI services, including requirement gathering, implementation, integration, evaluation, and production handover. This role works directly with customers to translate business requirements into secure, scalable, and production-ready AI applications that align with architectural standards and business objectives.
As a Forward Deployed Engineer, you will work closely with customers, Solution Architects, and Product Owners to turn solution designs into working AI applications. You will gather and document requirements, build and integrate AI services, run evaluation and testing, and support the solution through to go-live and handover, while maintaining high standards of quality, security, and cost efficiency.
Responsibilities
Work directly with customers to gather, clarify, and document business and technical requirements, and translate them into user stories, acceptance criteria, and agreed delivery scope.
Act as a technical point of contact during delivery: run workshops and demo sessions, present design options and progress, and report status to both technical and non-technical stakeholders.
Design, build, and deploy AI solutions on cloud AI services, including Generative AI applications, Retrieval-Augmented Generation (RAG), and Agentic AI workflows.
Integrate AI services with customer systems and data sources through APIs and data pipelines, working within their current environment constraints like identity, network, and security requirements.
Define and run model and system evaluation, apply guardrails and responsible-AI controls, and tune solutions for accuracy, latency, and cost.
Support solutions through UAT, go-live, and handover, including documentation, runbooks, and customer training, and handover to post-deployment support team of customers or GreenNode support team.
Qualifications
Bachelor's Degree in Computer Science, IT, or related field.
3-5 years of hands-on experience designing, building, implementing, and deploying cloud/software applications, including at least 2 years on AI/LLM-based solutions.
Required Skills
Good communication, facilitation, and presentation skills, with fluency in English, and the ability to explain technical concepts to non-technical stakeholders and present to senior audiences.
Experience gathering and documenting requirements, writing user stories with acceptance criteria, and managing delivery scope and change.
Familiarity with the software development life cycle (SDLC) and delivery.
Working knowledge of core cloud components: compute (VMs, containers, serverless), storage and database services, networking, basic security and identity and access management.
Strong programming skills in Python and at least one other popular programming language (TypeScript/JavaScript, Java, Go, C#, or similar), ideally applied to building AI-powered software (LLM applications, agents, RAG services, or data/ML pipelines) or comparable production software.
Solid software engineering fundamentals, including: Design, scaling, trade-offs; Clean, maintainable code structure and common design patterns; Data structures, algorithms, and API design (REST, async, streaming); Automated testing, debugging, and code review.
Hands-on experience delivering AI solutions on cloud AI services, including: Managed foundation model and LLM inference services; Managed agent runtimes or Agentic AI platform services; Agent orchestration frameworks and open protocols for tool and agent interoperability; Retrieval-Augmented Generation (RAG), embeddings, and vector search; LLM integration via APIs and SDKs, prompt engineering, and tool/function calling; Model evaluation, guardrails, and responsible-AI controls.
Experience integrating AI solutions into production systems, with proper security, cost optimization, and latency considerations.
Understanding of scalable AI infrastructure, such as GPU-enabled cloud workloads, inference, and model deployment pipelines.
Willingness to work at customer sites and travel when required.