Forward Deploy Engineer - AI Solutions

wits inovation lab; Hyderabad; On-site; INR 1,500,000 - 2,300,000; Full time

Job summary

WITS INOVATION LAB is seeking an AI solutions architect to collaborate with enterprise clients, design and deploy AI-powered systems, and translate business problems into actionable AI strategies that integrate with client workflows and data landscapes.

The role emphasizes rapid prototyping, productionizing, and iterating with client teams, building data connectors, and providing training to ensure adoption while feeding feedback to product roadmaps.

Qualifications

• Proven ability to design and deploy AI driven solutions for enterprise clients.
• Experience with LLMs, RAG, embeddings and vector databases.
• Experience with AWS/GCP/Azure and MLOps tooling.
• API design and integration with enterprise systems (Salesforce, ServiceNow).
• Understanding of SDLC and Agile methodologies.

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 prompting, memory management, tool usage, and behaviour planning with 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.

Job description

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.