Project Role: Technology Architect

Project Role Description: Design and deliver technology architecture for a platform, product, or engagement. Define solutions to meet performance, capability, and scalability needs.

Must have skills: Generative AI

Good to have skills: Python (Programming Language)Minimum 5 year(s) of experience is required

Educational Qualification: 15 years full time education

Summary:

We are seeking an experienced Full Stack Engineering Tech Lead with strong expertise in Generative AI, Agentic AI frameworks, and modern cloud-native application architectures.
The role involves leading the design and development of enterprise-scale AI platforms, including RAG pipelines, agentic AI workflows, and microservices-based backend systems. The candidate will work closely with product owners, architects, and engineering teams to build scalable AI-driven applications deployed on cloud platforms like AWS or GCP.
The ideal candidate should combine deep hands-on engineering expertise with technical leadership, driving innovation and mentoring engineers while building production-grade AI systems.

Role: Full Stack Engineering Tech Lead (GenAI / Agentic AI Platforms)

Roles & Responsibilities:

• Technical Leadership
• Lead the design, architecture, and development of AI-driven full stack applications.
• Provide technical direction and best practices for implementing Generative AI and Agentic AI solutions.
• Mentor and guide full stack engineers and AI engineers.
• Conduct architecture reviews, code reviews, and technical design discussions.
• Drive engineering excellence, scalability, and security standards across AI applications.
• AI / Gen

AI Platform Development:

• Architect and implement enterprise RAG (Retrieval Augmented Generation) pipelines.
• Design agentic AI workflows and orchestration pipelines using Lang Graph.
• Develop scalable LLM inferencing pipelines using open-source or enterprise LLMs.
• Design document ingestion pipelines including chunking, embedding, vectorization, and retrieval workflows.
• Evaluate and experiment with emerging AI standards and technologies such as MCP (Model Context Protocol).
• Design multi-agent orchestration frameworks for enterprise AI applications.
• Backend & Microservices Architecture
• Design and develop scalable microservices architecture using NestJS and Python.
• Define standards for REST API design, versioning, and secure API development.
• Implement event-driven integrations using webhooks and asynchronous communication patterns.
• Design DAG-based workflows and orchestration pipelines for AI processing pipelines.
• Data & AI Infrastructure
• Architect vector database solutions for semantic search and AI retrieval systems using:
• pg Vector
  • Open Search
  • Milvus
• Design metadata and operational data storage architecture using PostgreSQL / AWS RDS.
• Implement distributed data processing pipelines using Apache Spark or equivalent frameworks.
• Optimize embedding storage, indexing, and retrieval performance.
• Cloud & Platform Engineering
• Architect and deploy AI applications on AWS or GCP cloud platforms.
• Design cloud-native AI architectures leveraging containerized workloads and managed services.
• Define scalability, reliability, and resilience strategies for AI platforms.
• Collaborate with DevOps teams to implement CI/CD pipelines for AI application deployments.
• Security & Compliance
• Implement secure coding practices for APIs and AI applications.
• Ensure compliance with OWASP API security standards.
• Design secure AI pipelines ensuring data protection and access control.
• Establish security guardrails for AI integrations and data pipelines.
• Architecture & Design
• Translate functional business requirements into technical architecture and system design.
• Design RAG architecture, retrieval strategies, and agentic AI workflows.
• Develop architecture diagrams, solution blueprints, and system documentation using draw.io.
• Define design patterns for AI orchestration, microservices, and cloud-native deployments.

Professional & Technical Skills:

• AI & GenAI Technologies
• Lang Chain
• Lang Graph
• RAG pipeline architecture
• Agentic AI orchestration
• LLM inferencing pipelines
• Knowledge of emerging AI protocols such as MCP
• Programming Languages
• Python
• NestJS / Node.js
  Databases
• Vector Databases
• pg Vector
• Open Search
• Milvus
• Metadata Stores
• PostgreSQL
• AWS RDS
• APIs & Integration
• REST API development
• Webhooks
• Secure API design
• OWASP API security practices
• Data Processing
• DAG-based processing pipelines
• Apache Spark or distributed data processing frameworks
• Cloud Platforms
• AWS or GCP
• Tools
• draw.io
• Git-based development
• CI/CD tools
• Desired Skills
• Experience with LLMOps / MLOps practices
• Knowledge of prompt engineering and LLM evaluation
• Experience with semantic search and embedding optimization
• Exposure to multi-agent AI architectures
• Experience building enterprise knowledge assistants or AI copilots

Mandatory Project Experience:

Candidate must have hands-on implementation experience in enterprise AI systems, including at least one of the following:

• RAG-based enterprise knowledge assistant
• LLM inferencing platform
• Agentic AI workflow using Lang Chain / Lang Graph
• Document ingestion and semantic search pipeline
  Experience may come from industry projects, research initiatives, or AI platform development programs.
• Leadership & Soft Skills
• Strong technical architecture skills
• Ability to mentor engineers and guide development teams
• Hands on technical design and programming
• Strong problem-solving and analytical thinking
• Excellent communication and stakeholder management skills
• Ability to translate functional requirements into scalable technical architectures
• Strong innovation mindset and experimentation with emerging AI technologies

What We Value:

We value leaders who:

• Drive innovation in Generative AI and modern engineering practices
• Encourage experimentation and rapid prototyping
• Build scalable and secure enterprise AI platforms
• Foster continuous learning and technical excellence within engineering teams
  6–10 Years of exp.

Additional Information:

• The candidate should have minimum 5 years of experience in Generative AI.
• This position is based at our Mumbai office.
• A 15 years full time education is required.

15 years full time education

About Accenture

Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.
Visit us at www.accenture.com

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