Generative AI Architect- Manager Full-time

Line of Service
Advisory

Industry/Sector
Not Applicable

Specialism
Data, Analytics & AI

Management Level
Manager

Job Description & Summary
At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth.

Those in artificial intelligence and machine learning at PwC will focus on developing and implementing advanced AI and ML solutions to drive innovation and enhance business processes. Your work will involve designing and optimising algorithms, models, and systems to enable intelligent decision-making and automation.

Years of Experience: Candidates with 8+ years of hands on experience

Responsibilities:

Architecture Design:

• Design and implement scalable, secure, and high-performance architectures for Generative AI applications.

• Integrate Generative AI models into existing platforms, ensuring compatibility and performance optimization.

Model Development and Deployment:

• Fine-tune pre-trained generative models for domain-specific use cases.

• Data Collection, Sanitization and Data Preparation strategy for Model fine tuning.

• Evaluate, select, and deploy appropriate Generative AI frameworks (e.g., PyTorch, TensorFlow, Crew AI, Autogen, Langraph, Agentic code, Agentflow).

Innovation and Strategy:

• Stay up to date with the latest advancements in Generative AI and recommend innovative applications to solve complex business problems.

• Define and execute the AI strategy roadmap, identifying key opportunities for AI transformation.

Collaboration and Leadership:

• Collaborate with cross-functional teams, including data scientists, engineers, and business stakeholders.

• Mentor and guide team members on AI/ML best practices and architectural decisions.

• Should be able to lead a team of data scientists, GenAI engineers, devops and Software Developer.

Performance Optimization:

• Monitor the performance of deployed AI models and systems, ensuring robustness and accuracy.

• Optimize computational costs and infrastructure utilization for large-scale deployments.

Ethical and Responsible AI:

• Ensure compliance with ethical AI practices, data privacy regulations, and governance frameworks.

• Implement safeguards to mitigate bias, misuse, and unintended consequences of Generative AI.

Required Skills:

• Advanced programming skills in Python and fluency in data processing frameworks like Apache Spark.

• Should have strong knowledge on LLM’s foundational model (OpenAI GPT4o, O1, Claude, Gemini etc), while need to have strong knowledge on opensource Model’s like Llama 3.2, Phi etc.

• Proven track record with event-driven architectures and real-time data processing systems.

• Familiarity with Azure DevOps and other LLMOps tools for operationalizing AI workflows.

• Deep experience with Azure OpenAI Service and vector DBs, including API integrations, prompt engineering, and model fine-tuning. Or equivalent tech in AWS/GCP.

• Knowledge of containerization technologies such as Kubernetes and Docker.

• Comprehensive understanding of data lakes and strategies for data management.

• Expertise in LLM frameworks including Langchain, Llama Index, and Semantic Kernel.

• Proficiency in cloud computing platforms such as Azure or AWS.

• Exceptional leadership, problem-solving, and analytical abilities.

• Superior communication and collaboration skills, with experience managing high-performing teams.

• Ability to operate effectively in a dynamic, fast-paced environment.

Nice to Have Skills:

• Experience with additional technologies such as Datadog, and Splunk.

• Possession of relevant solution architecture certificates and continuous professional development in data engineering and GenAI.

Professional and Educational Background:

• BE / B.Tech / MCA / M.Sc / M.E / M.Tech / MBA

Education (if blank, degree and/or field of study not specified)
Degrees/Field of Study required:

Degrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills

Optional Skills
Accepting Feedback, Accepting Feedback, Active Listening, AI Implementation, Analytical Thinking, C++ Programming Language, Coaching and Feedback, Communication, Complex Data Analysis, Creativity, Data Analysis, Data Infrastructure, Data Integration, Data Modeling, Data Pipeline, Data Quality, Deep Learning, Embracing Change, Emotional Regulation, Empathy, GPU Programming, Inclusion, Intellectual Curiosity, Java (Programming Language), Learning Agility {+ 30 more}

Desired Languages (If blank, desired languages not specified)

Travel Requirements
0%

Available for Work Visa Sponsorship?
No

Government Clearance Required?
No

Job Posting End Date