Forward-Deployed AI Engineer

JOB SUMMARY

We are looking for a highly experienced Forward-Deployed AI Engineer who can work closely with customers, understand real-world business and technical requirements, and translate them into production-ready AI/ML solutions. This role combines AI engineering, software development, solution implementation, customer interaction, troubleshooting, and deployment.

KEY RESPONSIBILITIES

• Work directly with customers and technical stakeholders to understand business and technical requirements.
• Translate requirements into scalable AI/ML and software solutions.
• Design, develop, integrate, and deploy AI-powered applications.
• Work closely with platform, DevOps, and deployment teams to take solutions into production.
• Integrate AI/ML models with APIs, applications, databases, and enterprise systems.
• Build proof-of-concepts and rapidly convert them into production-ready implementations.
• Troubleshoot application, AI/ML, integration, and deployment issues.
• Participate in technical discovery, solution design, demonstrations, and customer discussions.
• Develop automation and reusable components to accelerate future deployments.
• Create technical documentation, deployment guides, and operational runbooks.
• Support onboarding, knowledge transfer, and technical training.
• Be willing to travel or work on-site when deployment requirements demand it.

SKILLS & QUALIFICATIONS

REQUIRED SKILLS

GOOD TO HAVE

• 8+ years in software engineering, AI/ML engineering, or a related technical field.

• Generative AI, LLMs, RAG, vector databases, or AI agents.

• Strong Python development experience.

• MLOps experience.

• Experience building and deploying AI/ML applications.

• Kubernetes/Helm-based deployments.

• Strong understanding of REST APIs, microservices, and integrations.

• Enterprise customer implementation experience.

• Experience with databases and data-processing pipelines.

• Solution engineering or technical consulting.

• Experience with AWS, Azure, or GCP.

• SaaS/product deployment experience.

• Docker and containerized application experience.

• Customer-site deployment experience.

• Working knowledge of Kubernetes.

• Strong Git, testing, CI/CD, and debugging fundamentals.

• Excellent customer-facing communication skills.

• Ability to turn ambiguous requirements into technical solutions.