Forward Deploy Engineer - AI Solutions

Responsibilities

• Collaborate directly with enterprise clients and internal stakeholders to deeply understand business goals, operational workflows, data landscapes, and technical constraints.
• Design, build, and deploy AI-driven solutions, integrating core AI platforms into customer systems and workflows.
• Translate complex business problems into viable AI solutions, focusing on where AI agents can augment or replace manual processes.
• Develop and maintain robust, scalable AI-powered systems, ensuring efficiency, reliability, and seamless integration with existing IT frameworks.
• Implement multi-agent systems and advanced AI solutions, utilizing techniques such as prompting, memory management, tool usage, and behaviour planning with Large Language Models (LLMs).
• Rapidly prototype and productionize solutions, working with client teams to whiteboard concepts, build prototypes, and iterate quickly based on feedback.
• Build connectors and data pipelines for secure and efficient data flow between client systems and AI platforms.
• Act as a technical solutions expert, providing troubleshooting, analysis, and support for AI-driven architectures.
• Provide training, documentation, and enablement to client business and operations teams, fostering self-sufficiency and adoption of AI tools.
• Serve as a critical feedback loop to internal product and engineering teams, influencing the roadmap based on customer insights and real-world deployment challenges.

Technical Skills

• Strong Programming Language Proficiency: Expert-level skills in at least one modern programming language (e.g., Python, Java).
• Strong AI Literacy: Demonstrable understanding of AI/ML fundamentals, including concepts like LLMs, RAG (Retrieval Augmented Generation), embeddings, and vector databases.
• Hands-on experience with cloud platforms (AWS/GCP/Azure), including familiarity with MLOps tooling.
• Experience with API design and integration for AI services and enterprise systems (e.g., Salesforce, ServiceNow).
• Solid understanding of software development lifecycle (SDLC) best practices and agile methodologies.

Good To Have

• Agentic AI Hands-on Experience: Practical experience in designing, building, and deploying AI agents or multi-agent systems that exhibit autonomous, proactive, and adaptive behaviours.
• Familiarity with containerization technologies (Docker, Kubernetes).
• Experience with data analytics and visualization tools.
• Prior experience in the commercial real estate or adjacent industries.