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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and deploying generative AI solutions on Microsoft Azure, utilizing advanced tools such as LangChain and LangGraph. Proven ability to lead engineering teams, manage project timelines, and ensure successful client deliverables.
Highest-signal resume keywords
Generative AI Solutions DesignAzure OpenAI Service DeploymentLangChain and LangGraph ExperiencePython and C#.NET DevelopmentLLMOps Management
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Generative AIAgentic SolutionsRetrieval-Augmented GenerationNatural Language ProcessingVector DatabasesTechnical ArchitectureProject ManagementModel EvaluationContext EngineeringConversational Workflows
Soft Skills
Team LeadershipClient CoordinationCoachingProblem SolvingFeedback Management
Tools & Technologies
Microsoft AzureAzure Kubernetes ServiceAzure API ManagementGitHub CopilotClaude Code
Certifications & Qualifications
Bachelor's Degree
Industry Keywords
AI SolutionsCloud Identity ManagementAgent OrchestrationMultiagent WorkflowsAI Application Deployment
Tech Stack
Tools & technologiesAzureCloudKubernetesPython.NET
About the role
Key responsibilities & impact- Lead client workstreams to design agentic and generative AI solutions on Microsoft Azure
- Translate business needs into technical architecture, delivery plans, budgets, and milestones
- Design agent orchestration and conversational workflows with LangChain, LangGraph, Model Context Protocol, and LLM APIs
- Develop retrieval-augmented generation pipelines using vector databases, natural language processing, and data science methods
- Direct implementation with Azure AI Services, Azure OpenAI Service, Python, and C#, connecting AI capabilities to Azure-native applications and APIs
- Oversee deployment and maintenance through LLMOps, Azure Kubernetes Service, Azure API Management, and cloud identity and access management
- Evaluate models and agent behavior through testing, LLM evaluation, and guardrails
- Guide engineers in AI-assisted development using GitHub Copilot and Claude Code
- Coordinate with clients and delivery teams to prioritize use cases, resolve technical dependencies, incorporate feedback, and track project progress
- Coach engineers through work reviews and address challenges with clients and colleagues
- Identify opportunities for innovation and improve delivery using firm methods and technology resources
Requirements
What you’ll need- At least a Bachelor's degree
- At least 5 years of experience
- Experience leading teams through the design, deployment, and maintenance of client generative AI and agentic solutions
- Experience with LangGraph, LangChain, and Model Context Protocol across multiagent workflows
- Experience building retrieval-augmented generation pipelines using vector databases, context engineering, and LLM APIs
- Experience deploying AI applications with Azure OpenAI Service, Azure Kubernetes Service, and Azure API Management
- Experience evaluating LLM outputs and guardrails while managing LLMOps testing and ongoing model performance
- Experience with Python and C#.NET development using GitHub Copilot and Claude Code
- Experience coaching engineering teams through feedback and code reviews while managing project timelines and client deliverables
- Ability to travel up to 80%
- Must not require, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth in PwC's policy
Benefits
Comp & perks- Annual discretionary bonus
- Medical insurance
- Dental insurance
- Vision insurance
- 401k
- Holiday pay
- Vacation
- Personal and family sick leave