Overview We are seeking an experienced Staff GenAI Developer to join our Corporate Generative AI CGAI Technologies team which serves as the CIT GenAI Center of Excellence. In this senior role you will drive the development of generative AI solutions covering use cases like intent processing retrieval augmented generation agentic actions and document summarization that empower our employees. You will provide technical leadership across teams to define and enforce best practices, bring a product driven mindset and ensure our GenAI platforms and applications are robust scalable and aligned with business needs. This role requires a hands-on leader with a passion for innovation in AI strong mentorship skills and deep expertise in Python LangChain Azure cloud services and vector databases for AI. Key Responsibilities Technical Architecture & System Design : Work with Architect to Design and implement core components of GenAI systems, including LLM agent orchestration, RAG pipelines, prompt‑engineering frameworks, and model‑fine‑tuning workflows. Make sound architectural decisions, evaluate alternative approaches, and ensure solutions meet performance, reliability, and scalability expectations for enterprise workloads. Hands-on Solution Development : Lead end‑to‑end development of GenAI solutions, from concept through production. Prototype and build critical components in Python, integrate LLMs and frameworks such as LangChain, and operationalize embeddings, vector stores, and RAG pipelines. Ensure AI systems effectively solve real‑world use cases and deliver measurable impact. Cross-Functional Collaboration : Partner with product managers, data scientists, and platform engineers to embed GenAI features into products and workflows. Drive cross‑team alignment, influence architecture across departments, and champion adoption of AI in high‑value use cases. Ensure GenAI efforts remain aligned with the broader enterprise technology strategy. Technical Leadership & Mentorship : Provide senior technical leadership and mentorship to engineers at all levels. Conduct code reviews, support pair programming, guide architectural discussions, and lead micro‑teams or pods to deliver complex features. Foster a collaborative, inclusive, and learning‑oriented engineering culture. Engineering excellence : Establish coding standards, enforce rigorous testing and documentation, and drive consistent CI adoption. Strengthen secure coding practices and maintain high test coverage across components. Ensure all solutions meet enterprise expectations for security, reliability, performance, and compliance. Apply strong engineering fundamentals end‑to‑end: write clean, maintainable, well‑tested code; follow modern design patterns; implement robust unit, integration, and functional tests; and ensure operational reliability through monitoring, observability, and resilient error handling. Review code developed by other engineers and provided actionable feedback to ensure adherence to best practices Agile Project Leadership: Lead and participate in Agile/Scrum ceremonies, including sprint planning, backlog refinement, and retrospectives. Manage work through Jira, optimize deployments via CI/CD pipelines (e.g., Jenkins), remove execution blockers, and maintain alignment across teams to ensure timely delivery of GenAI features. Product Mindset & Innovation: Identify opportunities where GenAI can create user value or improve workflows. Propose, design, and deliver innovative AI‑driven features and improvements. Anticipate future business needs, develop proof‑of‑concepts, and transition them into scalable production solutions. Balance rapid experimentation with sound architecture. Responsible AI & Governance: Ensure all GenAI solutions adhere to responsible AI principles. Integrate privacy, fairness, safety, and security considerations throughout the development lifecycle. Work with governance and security teams to establish guardrails and standard practices for safe enterprise deployment of LLMs. Continuous Learning & Thought Leadership: Stay current with emerging advancements in AI/ML—new LLMs, vector database improvements, open‑source frameworks, and cloud AI capabilities. Evaluate and adopt new techniques that strengthen the platform. Represent the GenAI team in knowledge‑sharing forums and communicate innovations to broader engineering groups and leadership
Experience : 6+ years of software development experience, including substantial hands-on work in AI/ML or GenAI projects (preferably at least 2–3 years focused on building applications with LLMs or related AI technologies). Prior experience as a tech lead or in a senior engineer role is expected, demonstrating ability to guide teams through complex projects. Technical Expertise : In-depth understanding of large language models and generative AI techniques – including how to implement and optimize LLM-based solutions (prompt engineering, fine-tuning models, working with embeddings and retriev