Apprentice Azure Ml Jobs (NOW HIRING)

We are seeking a highly motivated and innovative Forward Deployed Engineer to join our dynamic team. In this pivotal role, you will be at the forefront of our AI transformation journey, partnering directly with business process owners and technology leaders to fundamentally reimagine and re-engineer core business processes. You will help define principled approaches to agentic solution design and create reference solutions that leverage the power of Artificial Intelligence to set new standards for efficiency and innovation. 

The ideal candidate is a creative problem-solver with a unique blend of technical expertise, business acumen, and a passion for AI. You will act as the crucial bridge between business needs and technical solutions, identifying opportunities for AI-driven automation and bringing those concepts to life. A key part of your role will be to drive the adoption of these reference solutions within various business contexts and to apprentice future experts, ensuring the onward sustainability and scalability of our AI capabilities. You will achieve this by leveraging the full breadth and depth of Citi AI capabilities, including our growing set of AI agents. 

Key Responsibilities 

• Collaborate & Analyze: Work closely with business stakeholders to conduct in-depth analyses of existing business processes, workflows, and pain points. Identify and prioritize opportunities where AI can deliver maximum impact. 

• Solution Design & Prototyping: Design and rapidly prototype innovative AI-powered solutions. This includes developing proof-of-concepts (POCs) and where appropriate, minimum viable products (MVPs) to demonstrate feasibility and value. 

• Bridge Communication Gaps: Serve as a key technical translator and liaison between non-technical business users and core engineering teams, ensuring requirements are clearly understood and solutions are fit-for-purpose. 

• Stay Current: Maintain a deep understanding of the rapidly evolving AI landscape, including new tools, techniques, and best practices in machine learning, natural language processing, and generative AI. 

• Measure & Optimize: Define key performance indicators (KPIs) to measure the effectiveness and ROI of AI initiatives.  

• Documentation & Training: Participate in the creation of comprehensive documentation for new AI-driven processes and provide training and support to business users to ensure successful adoption. 

Qualifications & Required Skills 

• Professional Experience: 3-5+ years of experience in a hands-on technical role such as software engineering, data science, or machine learning engineering. 

• AI/ML Knowledge: Deep, hands-on experience with LLMs and AI agents as well as core machine learning concepts (both supervised and unsupervised), natural language processing (NLP), and data modeling. 

• Business Acumen: Demonstrated ability to understand business challenges and translate them into technical requirements and solutions. 

• Communication Skills: Exceptional interpersonal and communication skills, with the ability to articulate complex technical concepts to a non-technical audience. 

• Problem-Solving: A proactive and analytical approach to problem-solving, with a track record of delivering innovative solutions. 

Preferred Skills & Nice-to-Haves 

• Client-Facing Experience: Prior experience in a "forward deployed," consulting, or client-facing technical role is highly desirable. 

• Cloud Platforms: Hands-on experience with major cloud platforms (AWS, Google Cloud, Azure) and their associated AI/ML services (e.g., SageMaker, Vertex AI, Azure ML). 

• Data Engineering: Familiarity with data engineering principles, including ETL/ELT processes, data warehousing, and working with large datasets. 

• Domain Expertise: Knowledge of a specific business domain such as payments, finance and operations in financial services firms.