IN_Manager_Frontier Deployment Consultant (FDC)_GCC_Advisory_Gurgaon

Line of Service Advisory Industry/Sector FS X-Sector Specialism Operations 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 intelligent automation at PwC will focus on conducting process mining, designing next generation small- and large-scale automation solutions, and implementing intelligent process automation, robotic process automation and digital workflow solutions to help clients achieve operational efficiencies and reduce costs. *Why PWC At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities.

This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world.

We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life.

Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other.

Learn more about us .

At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law.

We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm’s growth.

To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations. " Role Summary Drive the design, development, and deployment of enterprise-grade agentic AI solutions built on a strong foundation of Java microservices, cloud-native architecture, and secure, scalable platforms.

The role blends Agentic AI engineering with modern backend engineering practices to deliver production-ready, resilient, and governed AI systems, along with the ability to contribute to end-to-end application layers.

Responsibilities THE MISSION Frontier models and autonomous agent frameworks have moved out of the lab and into the P&L.

The binding constraint is no longer model capability — it is deployment.

Most enterprise AI programmes stall in the gap between a pilot that impresses a steering committee and a system the business can actually run.

The Frontier Deployment Consultant exists to close that gap.

You will embed inside client environments — their tenancy, their data, their security review, their release process — and take a workflow from hypothesis to a production agentic system that keeps running after you leave the room.

This is a builder-advisor role in the literal sense.

You will hold the boardroom with structured business thinking and write the production code that makes the system real.

Candidates who have only ever done one of the two will not be a fit.

HOW THE ROLE OPERATES • Embedded, not adjacent.

You work inside the client's environment on their infrastructure and release cadence.

Expect 50–70% onsite presence, including travel across India, GCC hub cities and client HQ geographies where the engagement requires it.

•Pod delivery.

FDCs deploy in small pods — typically one Senior FDC plus two to three FDCs and engineers — with access to the practice asset library, PwC's Responsible AI framework and the GCC operating-model IP base.

•Outcome-owned.

Engagements are measured on time-to-value, reliability, adoption and realised ROI.

Delivery milestones are an input, not the score.

•Real enterprise conditions.

You will work under client security clearance, on client-issued devices where mandated, and inside regulated, data-resident and occasionally air-gapped environments.

WHAT YOU'LL DO 1.

Diagnose and shape value Partner with CEOs, COOs, CDOs, CTOs and business unit heads to find the workflows where agentic execution changes unit economics rather than shaving minutes.

Size the prize in terms a CFO will act on: cost-to-serve, cycle time, throughput per FTE, revenue leakage, total cost of ownership. 2.

Build 0→1 at startup velocity Form the hypothesis, diagnose the workflow with structured consulting toolkits, and put a working, interactive prototype in front of the client in days.

The proof is running software, not slideware. 3.

Architect production agentic systems Design and implement multi-agent architectures across brownfield estates: planner-executor patterns, agent handoffs, durable state and checkpointing, retries and cancellation, human-in-the-loop escalation.

Model Context Protocol (MCP) and agent-to-agent (A2A) integration.

Hybrid and graph-based retrieval over knowledge-graph and semantic-layer foundations. 4.

Own the evaluation and run layer Build the evaluation harness before the system ships — golden datasets, regression suites, task-completion and toolcall accuracy, groundedness and safety scoring, LLM-as-judge where it is defensible.

Instrument tracing end to end.

Define and hold service-level objectives for accuracy, latency, cost per task and containment rate. 5.

Engineer for the enterprise, not the demo CI/CD for non-deterministic systems, infrastructure as code, containerised deployment into client infrastructure, canary and rollback strategy, runbooks, incident response, and a documented handover that leaves the client's own team selfsufficient. 6.

Make it safe and defensible Agent identity and credentialing, least-privilege tool scoping, secrets management, prompt-injection and OWASP LLM Top 10 defences, PII and DLP controls, data residency, full audit trail.

Apply PwC's Responsible AI framework and map obligations to the DPDP Act