Forward Deployed AI Engineer

Keyrus is an international group of 3,000 experts across 30 countries, built on a single conviction: AI does not transform businesses. Architected intelligence does.

For more than 30 years, we have helped organizations build the data foundations that power intelligent systems.

Today, we go further by designing and operationalizing intelligence that delivers measurable business value.

Building AI capabilities is only part of the challenge. Real transformation happens when those capabilities work within existing business systems, data environments, workflows, and processes.

At Keyrus, you'll work closely with clients to turn AI opportunities into production-ready solutions, connecting engineering expertise with real business needs.

Technology amplifies. Keyrus culture differentiates. Industrial discipline connects the two.

• Location:
  
  United States (Remote)
• Contract:
  
  Permanent, full-time

As a Forward Deployed AI Engineer, you'll work directly with clients to take AI solutions from technical discovery through implementation, deployment, and adoption.

You'll combine hands-on software engineering, enterprise integrations, cloud technologies, and AI capabilities to deliver solutions that work in real client environments.

Your focus goes beyond writing code. You'll understand client challenges, define implementation plans, coordinate technical teams, and deliver measurable business results.

• Lead technical discovery with clients to understand their systems, data, workflows, and integration requirements.
• Translate business needs and approved architectures into practical implementation plans.
• Develop production-ready solutions integrating APIs, enterprise applications, cloud services, data platforms, and AI technologies.
• Collaborate with AI Engineers, Architects, and Data Engineers to resolve technical challenges and deliver integrated solutions.
• Own technical deployment and rollout within the agreed scope, ensuring reliable production performance.
• Work closely with client teams to troubleshoot issues, support adoption, and improve implemented solutions.
• Monitor performance, costs, and business outcomes while documenting reusable engineering practices.
• Turn successful implementations into reusable Keyrus assets, including integration patterns, deployment practices, technical documentation, and implementation guidance for future engagements.

You are a hands-on engineer with a strong consulting mindset who enjoys solving complex business and technical challenges. You develop production-quality code, understand enterprise integrations, and adapt solutions to real-world constraints. You are comfortable working directly with clients, managing evolving requirements, and taking ownership of technical delivery. You combine strong engineering skills with excellent communication, problem-solving, and collaboration.

• 5+ years of professional experience in software engineering, cloud engineering, enterprise integration, or related technical delivery roles.
• Hands-on experience developing, integrating, and deploying production software or AI-enabled solutions.
• Experience building and maintaining backend services, APIs, and enterprise integrations.
• Experience working with cloud platforms, deployment processes, and production environments.
• Ability to translate business requirements into technical implementation plans.
• Strong client-facing consulting experience, including communicating technical decisions and working with business stakeholders.

• Strong programming skills in Python, Type Script/JavaScript, Java, C#, or similar languages.
• Experience with REST APIs, backend services, authentication, and enterprise integrations.
• Hands-on experience with AWS, Azure, or Google Cloud.
• Knowledge of Git, CI/CD, testing, containers, and production monitoring.
• Familiarity with LLM APIs, RAG, AI agents, and GenAI application integration.
• Understanding of application security, system reliability, and cloud deployment practices.

• Experience developing production GenAI applications or agentic workflows.
• Familiarity with Lang Graph, MCP, OpenAI, Anthropic, or similar technologies.
• Experience with Kubernetes, Docker, or infrastructure as code.
• Background in backend, full-stack, data, or cloud engineering.
• Experience delivering solutions in regulated or complex enterprise environments.
• Previous experience in consulting, professional services, or client-embedded…