Agentic AI Engineer-Senior Associate-Analytics as service - Operate

Industry/Sector

Not Applicable

Specialism

Managed Services

Management Level

Senior Associate

Job Description & Summary

At PwC, our people in managed services focus on a variety of outsourced solutions and support clients across numerous functions. These individuals help organisations streamline their operations, reduce costs, and improve efficiency by managing key processes and functions on their behalf. They are skilled in project management, technology, and process optimization to deliver high-quality services to clients.

Those in managed service management and strategy at PwC will focus on transitioning and running services, along with managing delivery teams, programmes, commercials, performance and delivery risk. Your work will involve the process of continuous improvement and optimising of the managed services process, tools and services.

Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn’t clear, you ask questions, and you use these moments as opportunities to grow.

Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:

• Respond effectively to the diverse perspectives, needs, and feelings of others.
• Use a broad range of tools, methodologies and techniques to generate new ideas and solve problems.
• Use critical thinking to break down complex concepts.
• Understand the broader objectives of your project or role and how your work fits into the overall strategy.
• Develop a deeper understanding of the business context and how it is changing.
• Use reflection to develop self awareness, enhance strengths and address development areas.
• Interpret data to inform insights and recommendations.
• Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements.

Senior Associate – Agentic AI Engineer

Role: Senior Associate – Agentic AI Engineer
Level: Senior Associate

Tower: AI Engineering & Intelligent Automation (AI Managed Services)

Experience: 5–8 years

Key Skills: Agentic AI Workflow Development; LLM Orchestration; Python Engineering; API & Microservices; Cloud-Native AI Platforms (AWS Preferred); AI Guardrails & Evaluation

Educational Qualification:
Bachelor’s degree in Computer Science, Engineering, or related field (Master’s or relevant cloud/AI certifications preferred)

Work Location: Anywhere in India (Preferably Hyderabad / Bangalore)

Job Description

As a Senior Associate – Agentic AI Engineer, you will design, build, and operationalize agentic AI solutions using modern LLM orchestration frameworks and cloud-native architectures. You will work closely with senior engineers, architects, and operations teams to develop scalable, secure, and governed AI workflows that move reliably from development into production.

This role is hands-on and engineering-focused, with responsibilities spanning agent design, orchestration, evaluation, and release readiness within an enterprise AI managed services environment.

Key Responsibilities

Agentic AI Workflow Development

• Design and implement agentic AI workflows using frameworks such as LangGraph, CrewAI, AutoGen, and similar agent orchestration patterns.
• Build multi-agent systems that coordinate reasoning, tool use, memory, and task execution across complex workflows.
• Implement MCP (Model Context Protocol) tools and custom tool interfaces to extend agent capabilities.

LLM Orchestration & Prompt Engineering

• Orchestrate LLM interactions using LangChain and related frameworks across retrieval, tools, memory, and agents.
• Design, test, and optimize prompt strategies for reliability, performance, and cost efficiency.
• Support prompt versioning, experimentation, and controlled rollout strategies.

Backend & API Engineering

• Develop Python-based services and AI backends using FastAPI.
• Expose agent and workflow capabilities via secure, scalable REST APIs.
• Implement asynchronous workflows, background tasks, and event-driven processing where appropriate.

Cloud-Native AI Platform Development

• Build and deploy AI services on AWS, leveraging AWS Bedrock for foundation model access.
• Integrate supporting cloud services (e.g., IAM, logging, monitoring) to meet enterprise security and compliance requirements.
• Optimize solutions for performance, scalability, and cost in a cloud-native environment.

Containerization & Deployment

• Package AI services using Docker and deploy to Kubernetes environments.
• Support deployment pipelines that enable consistent builds across dev, test, and production.
• Collaborate with platform and operations teams to ensure production readiness.

State, Memory & Caching

• Design and implement agent memory and caching strategies using ElastiCache (Redis).
• Optimize retrieval, session state, and intermediate results for performance and reliability.

Observability, Guardrails & Evaluation

• Implement guardrails for safety, compliance, and reliability (input validation, output constraints, tool-use controls).
• Instrument workflows using Langfuse for tracing, evaluation, and observability.
• Build and maintain evaluation harnesses to validate quality, performance, and regression risks prior to releases.
• Support release gates and quality checks for AI workflow deployments.

Release, Versioning & Collaboration

• Contribute to release planning by validating AI workflow readiness and evaluation results.
• Use GitHub for version control, pull requests, code reviews, and documentation.
• Collaborate closely with architects, product owners, and operations teams to support smooth transitions to production.

Continuous Improvement & Learning

• Stay current with emerging agentic AI frameworks, orchestration patterns, and LLM capabilities.
• Identify opportunities to improve reliability, scalability, and developer experience across AI solutions.
• Contribute reusable components, patterns, and best practices to shared repositories.

Required Skills

• Strong Python development experience for AI and backend services.
• Hands-on experience with agentic AI frameworks (LangChain, LangGraph, CrewAI, AutoGen, or similar).
• Experience building APIs using FastAPI.
• Working knowledge of AWS cloud services, including AWS Bedrock.
• Experience with Docker and Kubernetes for containerized deployments.
• Familiarity with Redis / ElastiCache for caching or state management.
• Experience with prompt engineering, prompt testing, and optimization.
• Exposure to guardrails, observability, and evaluation for LLM-based systems.
• Proficiency with GitHub workflows and collaborative development practices.

Preferred Skills

• Experience implementing MCP tools or custom tool abstractions for agents.
• Hands-on use of Langfuse or similar AI observability platforms.
• Experience designing evaluation harnesses for LLM regression testing and release validation.
• Familiarity with enterprise AI governance, security, or compliance requirements.
• AWS certifications (Developer, Solutions Architect, or AI/ML specialty).

Travel Requirements

Not Specified

Job Posting End Date