Principal Consultant - Artificial Intelligence

Value Creed; Hyderabad; On-site; INR 3,500,000 - 5,200,000; Full time

Job summary

Value Creed seeks an experienced AI Architect to lead enterprise AI initiatives in the Energy Trading & Risk Management domain. You will architect AI-ready platforms, define governance guardrails, and drive scalable AI solutions for client value.

Responsibilities include leading design workshops, creating roadmaps, building data pipelines, and enabling AI adoption across trading operations and risk management.

Qualifications

• 8–13 years in enterprise software design/architecture.
• 2+ years delivering Generative AI and Agentic AI at scale.
• Minimum 6 years full stack application development.

Responsibilities

• Partner with clients to identify AI use cases and translate requirements into scalable technical solutions.
• Lead architecture discussions, solution design workshops, and governance reviews.
• Define and implement AI native enterprise architectures and roadmaps.
• Design AI-ready infrastructure with governance, security, observability, and guardrails.
• Establish reference architectures and reusable frameworks for GenAI/Agentic AI.
• Architect and implement scalable Agentic AI solutions using modern orchestration frameworks.
• Design multi-agent workflows, autonomous reasoning, tool integrations, and human-in-the-loop capabilities.
• Develop Retrieval-Augmented Generation architectures leveraging enterprise knowledge sources.
• Build scalable data pipelines and knowledge ingestion frameworks for AI workloads.
• Enable AI adoption across ETRM processes including trading ops and risk management.

Skills

AI Architecture

Generative AI

Agentic AI

Full stack development

Microservices

Kubernetes

LLMs/Foundational models

LangChain/LangGraph

Cloud platforms (Azure/AWS/GCP)

Security & governance

Tools

LangChain

LangGraph

Semantic Kernel

AutoGen

Orchestration frameworks

Job description

We are seeking an experienced AI Architect to lead the design and implementation of enterprise-grade AI solutions, with a strong focus on Agentic AI, Generative AI, and AI-native applications within the Energy Trading & Risk Management (ETRM) domain. The ideal candidate will be responsible for architecting AI-ready platforms, establishing robust AI governance and guardrails, and partnering with clients to design scalable, secure, and production-ready AI solutions that drive business value.

Key Responsibilities

• Partner with clients and business stakeholders to identify AI use cases and translate requirements into scalable technical solutions.
• Lead architecture discussions, solution design workshops, and technical governance reviews.
• Define and implement AI Native Enterprise Applications or Integrations on various tech stacks and cloud platforms, based on client needs.
• Define and implement enterprise AI architecture and technology roadmaps aligned with business objectives.
• Design and deploy AI-ready infrastructure with appropriate governance, security, compliance, observability, and responsible AI guardrails.
• Establish reference architectures, best practices, and reusable frameworks for GenAI and Agentic AI implementations.
• Architect and implement scalable Agentic AI solutions using modern orchestration frameworks.
• Design multi-agent workflows, autonomous reasoning systems, tool integrations, and human-in-the-loop capabilities.
• Develop Retrieval-Augmented Generation (RAG) architectures leveraging enterprise knowledge sources.
• Build scalable data pipelines and knowledge ingestion frameworks to support AI workloads if needed.
• Enable AI adoption across ETRM processes including trading operations, risk management, analytics, and decision support.

Required Skills & Qualifications

• 8-13 years of overall experience in enterprise grade software development, design and architecture.
• At least 2+ years of hands-on experience designing and delivering Generative AI and Agentic AI solutions at enterprise scale.
• Minimum 6 Years of hands-on full stack application development experience.
• Strong understanding of microservices, APIs, Kubernetes, event-driven architectures, and enterprise integration patterns.
• Expertise in Large Language Models (LLMs), foundation models, and Generative AI architectures.
• Hands-on experience designing and deploying Agentic AI applications in production environments.
• Deep expertise in Retrieval-Augmented Generation (RAG), vector databases, prompt engineering, and agentic workflows.
• Strong experience with LangChain, LangGraph, Semantic Kernel, AutoGen, or similar frameworks.
• Experience with Azure OpenAI, OpenAI, Anthropic, Gemini, or equivalent enterprise LLM platforms.
• Expertise in cloud-native architectures on Azure, AWS, or Google Cloud.