Description

About the Role: We are looking for a seasoned AI Tech Lead with deep hands-on experience in building and leading advanced Generative AI solutions. You will spearhead the design and development of innovative Gen AI Agents, Agentic Workflows, and AI-powered applications that address complex challenges in the multi-family business sector. Your expertise in Retrieval-Augmented Generation (RAG), vector databases, and Python frameworks such as LangChain will be critical in delivering scalable, production-grade AI systems. In this role, you will collaborate closely with Gen AI experts, product managers, and data engineers, driving the creation of reliable and scalable AI-driven products that have a tangible business impact.

Responsibilities:
• Architect and develop scalable full-stack Gen AI applications, including Agents and Agentic Workflows tailored to diverse business needs.
• Build and optimize feature engineering pipelines to extract meaningful insights from both structured and unstructured data, enhancing LLM-based product capabilities.
• Ensure data quality and readiness by implementing robust data cleansing and transformation processes for AI model consumption.
• Create feedback loops where AI outputs refine and enhance data sources, fostering continuous product improvement.
• Develop Python-based microservices for seamless orchestration and integration with Large Language Models (LLMs) and other AI components.
• Integrate and deploy machine learning models, including LLMs, RAG, and multi-modal AI, within cloud-native architectures.
• Design and maintain RESTful APIs to facilitate communication between system modules.
• Lead DevOps efforts by establishing CI/CD pipelines that support efficient and scalable deployment of Gen AI applications.
• Collaborate across multidisciplinary teams to deliver end-to-end Gen AI solutions.
• Stay abreast of advancements in LLMs, vector search technologies, prompt engineering, and retrieval methods to continuously elevate system performance.

Success Factors:
• Robustness: Deliver high-availability, fault-tolerant RAG pipelines and AI systems.
• Technical Mastery: Demonstrate deep Python expertise for microservices and AI integration.
• Data Excellence: Maintain high standards for data quality and preparation, enabling superior model performance.
• Operational Reliability: Implement strong monitoring and observability practices for minimal downtime.
• Collaborative Leadership: Communicate effectively and foster teamwork across AI experts, product teams, and engineers.
• Innovation Mindset: Keep pace with AI industry trends and proactively incorporate best practices.
• Agility: Adapt swiftly in a dynamic environment to continuously enhance AI-driven business solutions.

Core Skills:
• Bachelor’s degree in Computer Science, Computer Engineering, IT, or related field; advanced degrees preferred.
• 8-10 years of software engineering experience, with at least 5 years focused on applied AI/ML development.
• Proficiency in Python and experience with LangChain or comparable frameworks.
• Strong background in data processing, including transformation, cleansing, and feature engineering for AI/ML.
• Experience designing APIs, microservices, and distributed systems, particularly within AWS cloud environments.
• Solid understanding of MLOps/DataOps pipelines to support scalable AI/ML workflows.
• Expertise in logging, tracing, and observability frameworks to ensure system reliability.
• Hands-on experience with LLM fine-tuning, prompt engineering, and model evaluation.
• Familiarity with managed LLM platforms such as AWS Bedrock is a plus.
• Proven ability to work effectively in agile, cross-functional teams, collaborating closely with data engineers to ensure data quality and readiness

Key Skills

Education

Any Graduate