Senior Consultant - Generative AI Software Architect

Job Description

Are you a hands-on Architect who is passionate about the future of GenAI and eager to shape the next generation of intelligent, agentic applications? Our Corporate Generative AI Team is seeking a visionary Generative AI Architect to lead the design and implementation of cutting-edge GenAI and agentic AI solutions. This role is pivotal in defining the architecture and technical direction for enterprise-scale AI systems that power our internal corporate functions.

As a GenAI Architect, you will collaborate with cross-functional teams to build scalable, secure, and production-ready Corporate GenAI platforms and solutions. You will serve as a thought leader, influencing both technical strategies and executive-level decisions, while staying ahead of emerging trends in LLMs, AI agents, and orchestration frameworks.

Key Responsibilities

Enterprise GenAI Architecture & Strategy

• Define and evolve the enterprise-wide architecture blueprint for GenAI and agentic systems.
• Lead the design of modular, reusable, and scalable architecture patterns for GenAI and agentic applications.
• Design single pane of Glass GenAI product(s) which caters to multiple corporate domains and multiple personas.
• Develop and design robust, secure solution patterns that can be operationalized across enterprise environments.

Agentic AI Frameworks & Orchestration

• Architect and implement agentic AI systems using frameworks like LangGraph, LangChain, or CrewAI.
• Design agent coordination strategies and evaluation pipelines for autonomous enterprise workflows.

Prompt Engineering, Intent Understanding & Model Selection

• Develop architectural patterns for advanced prompt engineering, including dynamic prompt templates and multi-turn dialogue strategies.
• Implement intent analysis techniques to enhance agent decision-making and user interaction quality.
• Demonstrate deep understanding of various LLM models (e.g., GPT, Claude, Gemini, open-source models) and determine the right model for each use case based on performance, cost, latency, and compliance.
• Rapidly develop PoCs and iterate solutions using an agile, experimental approach—without compromising architectural integrity or long-term scalability.

Scalable Infrastructure & Deployment

• Build cloud-native, containerized infrastructure (Kubernetes, ECS, EKS) for deploying GenAI models at scale.
• Integrate CI/CD pipelines, model versioning, and automated testing for continuous delivery.

Enterprise Integration & Operationalization

• Design APIs and microservices to integrate GenAI capabilities into enterprise systems (ERP, CRM, HRIS).
• Architect solutions that are highly secure and have High availability, resiliency, uptime, and built-in insights.
• Establish monitoring frameworks for agent behavior, hallucination detection, and model drift.

Innovation & Thought Leadership

• Stay ahead of trends in agentic AI, autonomous systems, and LLM orchestration.
• Lead internal workshops, and innovation sprints to explore new use cases.

Documentation & Knowledge Sharing

• Maintain detailed architectural documentation and operational playbooks.
• Mentor engineering teams and promote best practices in GenAI development.

This is a hybrid position. Expectation of days in office will be confirmed by your Hiring Manager.

Qualifications

Basic Qualifications:

• 8+ years of relevant work experience with a Bachelor’s Degree or at least 5 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 2 years of work experience with a PhD, OR 11+ years of relevant work experience.

Preferred Qualifications:

• 9 or more years of relevant work experience with a Bachelor Degree or 7 or more relevant years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 3 or more years of experience with a PhD
• 5+ years of experience as a software architect, in designing and implementing scalable, secure, and resilient architectures for enterprise-grade global applications.
• 3+ years of hands-on experience in architecting and deploying AI, ML, GenAI based enterprise solutions, including the integration of large language models (LLMs) and agentic frameworks to automate complex workflows, enhance decision-making, and deliver personalized user experiences.
• Proven track record of delivering highly resilient enterprise solutions.
• Proven architectural expertise in building conversational agents with short-term memory (context windows, session state) and long-term memory (vector stores, memory graphs).
• Deep architectural knowledge of LLM orchestration frameworks (e.g., LangGraph, CrewAI, Semantic Kernel) and multi-agent systems.
• Familiarity with multi-agent GenAI solutions that incorporate agentic behaviors using A2A and MCP protocols.
• Experience with vector databases (e.g., Pinecone, ChromaDB), embedding models, and RAG pipelines.
• Experience in retrieval-augmented generation (RAG) pipelines, hybrid search strategies, and embedding optimization.
• Experience with DevOps/MLOps practices, CI/CD pipelines, and version control systems.
• Proven ability to lead cross-functional AI initiatives, including PoC development, stakeholder alignment, and enterprise rollout.
• Excellent communication skills with the ability to translate complex technical concepts to business stakeholders.

Technical Skills:

• Languages & Frameworks: Python, FastAPI, PyTorch, LangChain, LangGraph, CrewAI
• Cloud & Infrastructure: AWS, Azure, Docker, Kubernetes, ECS, EKS
• MLOps & DevOps: MLflow, Databricks, Airflow, Ray, Git, CI/CD pipelines
• LLM & GenAI Tools: OpenAI, Claude, Gemini, Hugging Face Transformers, RAG
• Databases & Storage: Pinecone, ChromaDB, Redis, PostgreSQL
• Orchestration & Agents: Semantic Kernel, multi-agent coordination, memory management, MCP, A2A.
• Monitoring & Governance: Prometheus, Grafana, audit logging, access control
• Frontend: ReactJS, HTML, CSS, JavaScript