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Applied AI Engineer II

Deloitte Atlanta, GA

Atlanta, GA

Today

$103k - $189k/yr Full time AI Applied Engineer

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Job Description

At Deloitte, the on-site Applied AI Engineer II in Atlanta helps turn ideas into full‑stack products powered by GenAI and agentic capabilities. You’ll collaborate across product and AI investments to deliver outcomes that matter, guiding ideas from concept through production with a strong emphasis on quality and impact. This role offers a competitive annual salary range of USD 102,500 to 188,900, onsite work in Atlanta, and eligibility for a discretionary annual incentive program. You’ll join a team that values practical engineering, measurable results, and close collaboration with cross‑functional partners.

Responsibilities

Outcome driven accountability: develop engineering solutions that address complex problems with meaningful business value, maintaining lean designs and controlling inference, token, and cloud costs.
Technical leadership and advocacy: act as the technical champion for products, ensuring code integrity, feasibility, and alignment with business and customer goals; participate across requirements, design, development, testing, integrations, and support.
Engineering craftsmanship: uphold code and design integrity, align implementation with architecture and tech stack, ensure quality and maintainability; be hands‑on, continuously learn new approaches, and produce technical specifications and scalable, well‑documented code that meets quality KPIs; collaborate effectively with diverse teams.
Customer centric engineering: develop lean solutions through rapid, low‑cost experimentation to solve customer needs; engage with customers and product teams before, during, and after delivery to ensure timely and appropriate solutions.
Incremental and iterative delivery: prioritize action and evidence over extensive planning; navigate complexity with a forward‑leaning approach to deliver maintainable solutions.
Cross‑functional collaboration and integration: work with product management, design, and delivery teams; balance feasibility, viability, usability, and value by integrating diverse perspectives; foster a collaborative environment that enhances innovation.
Advanced technical proficiency: apply modern software engineering practices including AI and agentic SSDLC to deliver frequent product deployments with full automation from discovery through production and operations, supported by quality checks throughout the lifecycle; model and promote these techniques to improve solutioning and delivery; focus on continuous improvement and lifecycle understanding.
Domain expertise: quickly acquire domain knowledge relevant to the business or product and translate business needs, architectures, and UX/UI designs into technical specifications and code; contribute as a flexible, quality‑focused team member, mindful of tech debt payoff.
Effective communication and influence: articulate complex technical concepts clearly, persuading teammates and product teams with evidence and well‑structured trade‑offs; craft narratives that align technical solutions with business objectives.
Engagement and collaborative co‑creation: engage with product engineering teams at all levels and with customers as needed; cultivate constructive relationships and a culture of co‑creation to achieve product goals.

Requirements

Ability to work independently and as part of a team
Strong written and verbal communication skills
Meticulous attention to detail and quality of work
Ability to build and sustain professional relationships
Ability to lead projects or workstreams
Ability to manage and prioritize multiple tasks in a fast paced environment
Strong interpersonal skills and professional demeanor
Ability to meet deadlines and 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 Angular, React, NodeJS, Python, C#, .NET, Java, SQL/NoSQL, PyTorch, TensorFlow, LangChain, LangGraph, and unit testing frameworks
2+ years 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 cloud‑native engineering using FaaS, PaaS, or microservices on Azure, AWS, or GCP, including AI/ML services (Azure OpenAI, AWS Bedrock, Vertex AI) and infrastructure‑as‑code with FinOps accountability
Experience with business context diagrams, sequence/activity/state/entity relationship/data flow diagrams, OOP/OOD, data structures, algorithms, and AI‑augmented spec‑driven development
Familiarity with XP, Lean, DevSecOps, SRE, ADO, GitHub, SonarQube, MLflow, and agentic AI frameworks (eg LangFuse, LangSmith) for rapid, high‑quality product delivery
Ability to travel approximately 10% depending on project needs
Limited immigration sponsorship may be available

Technologies

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

Benefits

Discretionary annual incentive program

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4d ago

Applied AI Engineer II - Encore Program

Deloitte New York, NY

New York, NY

4d ago

Full time AI Applied Encore

Apply Now

Job Description

Based in New York on-site, Deloitte's Encore Program seeks an Applied AI Engineer II to advance hands-on full-stack development and embed GenAI and agentic capabilities into customer-focused products. The role collaborates with cross-functional teams to design, build, and ship end-to-end solutions that deliver tangible outcomes, with a bachelor’s degree and at least two years of relevant experience expected for candidates.

Responsibilities

Outcome-Driven accountability: Own and promote accountability for customer and business outcomes, including the cost of achieving them. Develop engineering solutions to complex problems that yield valuable outcomes, ensuring lean designs and implementations, and overseeing 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. Participate in requirement analysis, component design, development, testing, integrations, and support.
Engineering craftsmanship: Maintain accountability for code-design integrity, adherence to architecture and tech stack, quality, data, and ongoing maintenance. Be hands-on and self-driven, continually learning new approaches, languages, and frameworks. Create technical specifications and deliver high-quality, scalable code that meets quality KPIs, while collaborating with diverse teams.
Customer-centric engineering: Develop lean engineering solutions through rapid, inexpensive 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, using a leaning-forward mindset to navigate complexity and uncertainty while delivering lean, maintainable solutions.
Cross-functional collaboration and integration: Work with empowered, cross-functional teams including product management, experience, and delivery. Integrate diverse perspectives to balance feasibility, viability, usability, and value, fostering a collaborative environment that enhances innovation.
Advanced technical proficiency: Apply modern software engineering practices and principles, including AI and agentic SDLC, to enable daily product deployments with full automation from discovery to production through the SDLC lifecycle and quality checks.
Domain expertise: Rapidly acquire domain knowledge relevant to the business or product. Translate business needs, architectures, and UX/UI designs into technical specifications and code, contributing as a flexible, quality-focused team member.
Effective communication and influence: Clearly articulate complex technical concepts, inspiring teammates and product teams through evidence-based trade-offs and coherent narratives aligned with business objectives.
Engagement and co-creation: Collaborate with product engineering teams at all levels, including customers as needed. Build constructive relationships and drive consensus toward feasible, value-driven 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
Ability to build and sustain professional relationships
Ability to lead projects or workstreams
Ability to manage and prioritize multiple tasks in a fast-paced environment
Strong interpersonal skills and professional demeanor
Ability to meet deadlines
Ability to provide clear guidance to others
Ability to travel approximately 10% depending on 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
Azure, AWS, GCP, Azure OpenAI, AWS Bedrock, Vertex AI
DevSecOps, SRE, ADO, GitHub, SonarQube, MLflow

Benefits

You may be eligible to participate in a discretionary annual incentive program, subject to program rules. Any award, if given, depends on individual and organizational performance.

The Team

US Deloitte Technology Product Engineering modernizes software and product delivery into a scalable, cost-effective model focused on value and outcomes. As Deloitte's primary internal development group, Product Engineering delivers innovative digital solutions to businesses, service lines, and internal operations, supporting Deloitte’s continued success as an engine of its operations.

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