Lead AI Engineer (Agentic AI Applications)

Preferrable: No Data Scientists pls, mandate skills: AI, ML, Python/Java, Kafka, Data Engineering background with application development 1. Led App Development teams and are aware of working with distributed systems 1. Are well aware of architecture (backend) and integrations 1. Taking Applications to production (so awareness of end to end working of systems) 1. Preferably know Kafka 1. Preferably worked as Data Engineering Leads 1. Are tech savvy, have tried out building Gen AI apps. Ideal Candidate Traits • Owns outcomes — drives initiatives from concept to production with accountability and focus. • Thinks like a product builder — connects engineering work to user and business value. • Strong in distributed systems and applied AI — delivers scalable, production-ready solutions. • Acts with curiosity and bias for action — proactive, self-directed, and solution-oriented. • Clarifies ambiguity — asks the right questions and brings structure to complex problems. • Communicates with clarity and influence across technical and product teams. • Passionate about impact — builds intelligent, reliable systems that make a difference. Role Overview Ascend Learning is seeking a Lead AI Engineer (Contract) who is a driver, not an order taker — someone who leads from the front, manages delivery across the AI team, and ensures successful execution of complex, high-impact AI initiatives. You will architect and deliver applied AI solutions powered by Large Language Models (LLMs) and Small Language Models (SMLs) within a distributed, production-grade ecosystem. This is a hands-on technical leadership and delivery management role that combines engineering excellence, team guidance, and cross-functional collaboration. You will work closely with Technical Product Owners (TPOs), Technical Program Managers (TPMs), Platform Engineering, and Senior Managers to deliver scalable, reliable, and innovative AI applications that transform digital learning experiences. Roles and Responsibilities · Delivery Management & Leadership: Manage delivery of AI engineering initiatives, ensuring projects are executed on time, within scope, and to high quality standards. Coordinate engineers and workstreams, resolve dependencies, and drive accountability. · Technical Leadership & Team Guidance: Lead and mentor AI engineers in architecture, design, and implementation of best practices. Set engineering standards for quality, reliability, and maintainability. · AI Solution Design & Development: Architect and develop Agentic AI applications using LLMs and SMLs for automation, reasoning, and content generation. Build distributed backend systems with Python, Fast API, Azure, Kafka, and Kubernetes. · Cross-Functional Collaboration: Partner with Technical Product Owners, Technical Program Managers, and Platform Engineering to define scope, success metrics, and optimize infrastructure and performance. · Innovation & Strategic Thinking: Stay current on advancements in LLMs, SMLs, RAG, and Agentic AI frameworks. Experiment with OpenAI and Azure AI tools and promote technical innovation balanced with predictable delivery. · Productionization & Lifecycle Management: Lead productionization of AI application, ensuring reliability, observability, and lifecycle management of deployed solutions. Qualifications · Education & Experience: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a closely related field—or equivalent practical experience. Minimum of 7 years in software or AI engineering, with at least 2 years in technical leadership or architectural roles, demonstrating a proven track record of delivering complex solutions. · Delivery Management Expertise: Demonstrated success managing end-to-end delivery for engineering teams or overseeing multi-stream technical projects, ensuring timely execution, high standards, and effective coordination across stakeholders. · Technical Proficiency: Deep expertise in designing and implementing distributed systems, microservices architectures, and event-driven solutions. Hands-on experience with production-grade AI systems leveraging Large Language Models (LLMs) and Small Language Models (SMLs). · Technology Stack Mastery: Advanced proficiency in Python, FastAPI, and Azure Cloud. Skilled in deploying and orchestrating solutions with Docker and Kubernetes. Familiarity with LangChain, LangGraph, vector databases, and Retrieval-Augmented Generation (RAG) pipelines. · DevOps & Observability: Strong understanding of CI/CD pipelines, monitoring, logging, and tracing using tools like Datadog. Experienced with modern DevOps best practices to ensure system reliability and maintainability. · Additional Competencies: Working knowledge of OpenAI APIs and the Azure ecosystem, including Cosmos DB, AI Search, and Cognitive Services. Familiarity with front-end frameworks (Angular, React) and principles of UI/UX design, enabling seamless integration of intelligent backends with web applications. Exceptional communication, collaboration, and leadership abilities, with a passion for mentoring teams and driving impactful results.