Applied AI Engineer II

Deloitte seeks an Applied AI Engineer II in New York, NY onsite, combining hands-on full-stack software engineering with applied AI to embed GenAI and agentic capabilities into products.

Responsibilities

• Outcome-Driven Accountability: embrace a culture of accountability for customer and business outcomes and the cost of achieving them; design engineering solutions that solve complex problems with measurable value, delivering lean, high-quality designs and implementations, and owning inference, token, and cloud costs.
• Technical Leadership and Advocacy: act as the technical advocate for products, ensuring code integrity, feasibility, and alignment with business and customer goals; contribute across requirements analysis, component design, development, testing, integrations, and support.
• Engineering Craftsmanship: maintain accountability for code-design integrity, architecture fidelity, data handling, quality, and ongoing operations; be hands-on, self-driven, and continually learn; create technical specifications and produce high-quality, scalable code that meets quality KPIs; collaborate effectively with diverse teams.
• Customer-Centric Engineering: develop lean engineering solutions through rapid, low-cost experimentation to address customer needs; engage with customers and product teams before, during, and after delivery to ensure the right solution is delivered at the right time.
• Incremental and Iterative Delivery: favor action and evidence over extensive planning; navigate complexity with a forward-leaning approach to deliver lean, maintainable solutions.
• Cross-Functional Collaboration and Integration: work with product management, experience, and delivery teams; integrate diverse perspectives to balance feasibility, viability, usability, and value; foster a collaborative environment that enhances team synergy and innovation.
• Advanced Technical Proficiency: demonstrate expertise in modern software engineering practices, including AI and agentic SDLC to enable daily product deployments with full automation from discovery to production to operations, with quality checks through the SDLC; model best practices to optimize solutioning and delivery; emphasize continuous improvement across the lifecycle.
• Domain Expertise: quickly acquire domain knowledge relevant to the business or product; translate business/user needs, architectures, and UX/UI designs into technical specifications and code; be a flexible, quality-focused team member supportive of teammates and focused on tech debt payoff.
• Effective Communication and Influence: articulate complex technical concepts clearly; inspire and influence teammates and product teams with evidence-based trade-offs; craft cohesive narratives that align technical solutions with business objectives.
• Engagement and Collaborative Co-Creation: engage with product engineering teams at all levels, including customers as needed; build constructive relationships fostering co-creation and momentum toward product goals; align diverse perspectives to create feasible solutions.

Requirements

• Ability to work independently and as part of a team
• Effective written and verbal communication skills
• Meticulous attention to detail and quality of work product
• Ability to build and sustain professional relationships
• Ability to lead projects or workstreams
• Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
• Strong interpersonal skills and professional demeanor
• Ability to meet deadlines
• Ability to provide clear guidance to others
• Bachelor's degree in computer science, software engineering, data science, machine learning, or related discipline
• 3+ years of experience with most of the following: Angular, React, NodeJS, Python, C#, .NET, Java, SQL/NoSQL, PyTorch, TensorFlow, LangChain, LangGraph, plus unit testing frameworks
• 2+ years of experience building AI/ML and agentic applications, with hands-on GenAI experience across LLM integration (OpenAI, Anthropic, or open-source models), RAG pipelines, prompt engineering, vector databases, evaluations, and AI agent orchestration
• 2+ years of experience with cloud-native engineering using FaaS, PaaS, or micro-services on Azure, AWS, or GCP, including AI/ML services such as Azure OpenAI, AWS Bedrock, or Vertex AI, plus infrastructure-as-code and FinOps-aware cost engineering
• Prior software engineering experience with Business Context Diagrams, sequence/activity/state/entity relationship/data flow diagrams, OOP/OOD, data structures, algorithms, and code instrumentation, and AI-augmented spec-driven development
• Prior experience with XP, Lean, DevSecOps, SRE, ADO, GitHub, SonarQube, MLflow, and agentic AI frameworks (eg LangFuse, LangSmith) or equivalent multi-agent orchestration tools to deliver high-quality products rapidly
• Ability to travel approximately 10 percent, depending on client engagements
• Limited immigration sponsorship may be available

Technologies

• Angular
• React
• NodeJS
• Python
• C#
• .NET
• Java
• SQL
• NoSQL
• PyTorch
• TensorFlow
• LangChain
• LangGraph
• OpenAI
• Anthropic
• LangFuse
• LangSmith
• AWS
• Azure
• GCP
• Vertex AI
• Azure OpenAI
• AWS Bedrock
• MLflow
• GitHub
• SonarQube
• ADO (Azure DevOps)

The Team

US Deloitte Technology Product Engineering has modernized software and product delivery, creating a scalable, cost-effective model that focuses on value and outcomes, supported by a progressive and responsive talent structure. As Deloitte's primary internal development team, Product Engineering delivers innovative digital solutions to businesses, service lines, and internal operations with proven bottom-line results and outcomes, powering Deloitte's success.