Project Role : Large Language Model Architect
Project Role Description : Architect large language models (LLM) that can process and generate natural language. Design neural network parameters, trained on large quantities of unlabeled text data.
Must have skills : Large Language Models (LLMs)
Good to have skills : NA
Minimum 18 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
As a Large Language Model Architect, you will engage in the innovative design and development of advanced language models that are capable of understanding and generating human-like text. Your typical day will involve collaborating with cross-functional teams to define project requirements, conducting research to enhance model performance, and iterating on designs based on feedback and testing results. You will also be responsible for analyzing large datasets to inform model training and optimization, ensuring that the models meet the highest standards of accuracy and efficiency. Your role will be pivotal in pushing the boundaries of natural language processing and contributing to groundbreaking advancements in the field.
We're looking for a Platform PM to own the product roadmap for an enterprise agentic AI platform at Accenture.
Roles & Responsibilities:
- Architect large language models that can process and generate natural language.
- Design neural network parameters, trained on large quantities of unlabeled text data.
- Collaborate with data scientists and engineers to integrate models into applications.
- Conduct performance evaluations and optimize models based on testing results.
- Stay updated with the latest advancements in natural language processing and machine learning.
- Mentor junior professionals in best practices for model development and deployment.
-Lead complex, multi-workstream AI transformation programs from initiation through deployment and scaling
-Coordinate cross-functional teams including engineers, architects, product managers, and business stakeholders to drive delivery
-Establish and manage program governance, risk management, and delivery frameworks tailored to AI-native ways of working
-Navigate and guide AI-native development practices where specifications emerge from building, not upfront documentation
-Maintain technical fluency to engage credibly with complex software engineering challenges including distributed systems, agentic workflows, semantic technologies, and platform architectures
-Assess and communicate technical risks specific to AI systems (model drift, hallucinations, data quality, performance at scale)
-Drive stakeholder alignment across senior leadership, ensuring clarity on objectives, progress, risks, and value realization
-Navigate organizational complexity and remove blockers to maintain program momentum and team velocity
-Define and track delivery metrics, KPIs, and business outcomes to demonstrate transformation impact
-Champion agile/lean delivery practices and continuous improvement across transformation teams, adapting traditional methodologies for AI-native contexts
-Manage program budgets, resource allocation, and vendor relationships for AI initiatives Partner with architects to ensure delivery approaches support platform engineering principles and reusability across initiatives.
-This is an inward-facing product role. Your customers are the business process teams who will build and run agents on the platform. You'll translate their needs into a coherent platform roadmap, own the product backlog, manage monthly releases, and hold the line on scope. You'll work closely with the Technical Architect and Head of Engineering to decide what gets built, in what order, and why.
-We're looking for someone with 8–10 years in product management, at least 3 years on technical platforms or infrastructure products, and enough familiarity with AI and data systems to write meaningful specs and challenge engineering estimates.
-Experience with agentic AI or LLM-based products is a strong plus.
Professional & Technical Skills:
- Must To Have Skills: Proficiency in Large Language Models (LLMs).
- Experience with natural language processing frameworks and libraries.
- Strong understanding of neural network architectures and training methodologies.
- Familiarity with data preprocessing techniques for text data.
- Ability to analyze and interpret model performance metrics.
-Complex Program Management
-AI Transformation Delivery
-AI-Native Development Practices
-Complex Software Engineering Understanding
-Technical Architecture Literacy
-AI/ML Systems Understanding
-Platform Engineering Principles
-Distributed Systems & Microservices
-Agile & Lean Methodologies
-Stakeholder Management
-Risk & Change Management
-Resource & Budget Management
-Cross-Functional Team Leadership
-Business Value Articulation
-Vendor & Partner Management
-Organizational Change Management
-Executive Communication
-Delivery Metrics & Reporting
-Execution Catalyst: Turns vision into reality by orchestrating people, technology, and processes to deliver complex transformations successfully
-Strategic Operator: Balances big-picture thinking with tactical execution, ensuring programs stay aligned to business goals while navigating day-to-day complexity
-Technical Translator: Bridges technical and business domains with deep understanding of AI complexity, enabling credible engagement with both engineers and executives
-Trust Builder: Creates confidence across all levels of the organization through transparent communication, proactive risk management, and consistent delivery
-Fluency in agentic AI architecture patterns — planning and routing, tool and function calling, multi-step reasoning, long-term memory, human-in-the-loop, retries and guardrails, and multi-agent orchestration
-Comfort reading technical specs, system diagrams, and code at a level sufficient to partner credibly with a Technical Architect and Head of Engineering prototyping in Python or notebooks is a plus
-Demonstrated ownership of the full product lifecycle — roadmap, monthly and quarterly release planning, backlog grooming, launch & post-launch iteration
-Cross-functional delivery leadership without direct authority — aligning platform engineering, data and business-process owners
-Exceptional written communication — ability to produce crisp PRDs, interface specs, decision memos, RFCs, exec updates
Additional Information:
- The candidate should have minimum 20+ years of experience in Large Language Models (LLMs).
- This position is based at our Bengaluru office.
- A 15 years full time education is required.
