Forward Deployed AI Engineer, Keyrus

• You are a hands-on engineer who thinks like an architect and acts like a builder. You are comfortable working closely with the client, the problem, and the delivery, and you make sound decisions in complex, evolving environments
• You enjoy solving operational challenges, not only exploring technical concepts
• You communicate clearly with both technical teams and senior business stakeholders
• You navigate ambiguity with confidence, validate assumptions, and adapt quickly
• You take ownership of outcomes and raise risks or changing priorities early
• You understand that AI value depends on the full system: data, workflows, governance, adoption, and measurement
• You naturally look for what can be reused, improved, and scaled
• 5–10 years of relevant experience in AI Engineering, Machine Learning, Software Engineering, Data Engineering, or technical consulting
• Hands-on experience delivering AI, GenAI, or software solutions into production
• Experience working directly with clients or in complex stakeholder environments
• Evidence of turning complex use cases into adopted, measurable solutions
• A degree in Computer Science, Engineering, Artificial Intelligence, Data Science, or a related field, or equivalent practical experience
• Ability to work effectively in multidisciplinary environments
• Professional proficiency in English
• Strong Python development skills, API integration experience, and modern software-engineering practices
• Hands-on experience with Large Language Models (LLMs), GenAI architectures, prompt workflows, and model/provider selection
• Experience with RAG, embeddings, vector search, AI agents, and agentic workflows
• Familiarity with frameworks such as LangChain, LlamaIndex, LangGraph, Semantic Kernel, AutoGen, or comparable tools
• Experience integrating AI into enterprise systems, APIs, and business workflows
• Experience with at least one major cloud platform: Azure, AWS, or GCP
• Working knowledge of Docker, Git, CI/CD, production deployment, monitoring, and evaluation
• Understanding of MLOps / LLMOps, security, data privacy, governance, and Responsible AI principles

Desirable

• 🗓 Target start date: September 2026
• ⏰ Working hours: Full-time (40h/week)
• As a Forward Deployed AI Engineer, you work at the heart of a client's most pressing AI challenges, turning intent into an operational, measurable result in weeks rather than months
• This is an experienced individual-contributor role for someone who combines hands-on engineering, architectural judgment, and business understanding
• You own the problem from ambiguity through to execution - understanding the real context, building and deploying the solution, and proving, not declaring, that it creates value
• Once the terrain is understood, you become the reference the team relies on to make that result last
• Co-create solutions with business and technical stakeholders through workshops, rapid iterations, and hands-on delivery
• Locate, qualify, and secure access to the data required for each use case, working directly with Data Engineers
• Translate use cases into production-ready GenAI and agentic AI solutions, including RAG architectures, intelligent assistants, and AI-enabled workflows
• Prototype, test, deploy, monitor, and improve solutions in real client environments using feedback from users and domain experts
• Work with Data Engineers, Software Engineers, Foundations Architects, Governance experts, Business Value Advisors, and Service Delivery Managers to deliver sustainable outcomes
• Balance speed, quality, cost, security, and maintainability while making clear technical and delivery trade-offs
• Define success criteria from the outset, including adoption, performance, reliability, risk, cost, and measurable business value
• Ensure solutions are documented, governed, and transferable so clients can operate them with confidence
• Turn successful delivery into reusable patterns, accelerators, and building blocks that strengthen future engagements
• ⭐ What Makes You Successful:
• You combine technical credibility, pragmatism, and end-to-end ownership
• You focus on real-world outcomes, adoption, and measurable value—not only the solution itself
• You move quickly while balancing speed, quality, cost, and risk
• You build trust and become a reliable partner in complex client environments
• You operate effectively under pressure in client environments, where progress and results are continuously visible
• You know when to go deep technically and when to orchestrate the right expertise
• You continuously improve, reuse, and scale what works across engagements