Role: Forward Deploy Engineer - AI Solutions
Industry Type: IT Services & Consulting
Department: Engineering - Software & QA
Employment Type: Full Time, Permanent
Role Category: Quality Assurance and Testing
UG: Any Graduate
PG: Any Postgraduate
Essential Duties And 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.