AI Solutions Architect

P2pro Technology Solutions; Hyderabad; On-site; INR 1,100,000 - 1,600,000; Full time

Job summary

P2pro Technology Solutions is seeking a senior AI/ML engineer in Hyderabad to design and implement enterprise AI architectures. You will lead discovery sessions, build production-grade AI apps in Python, and integrate with CRM/ERP systems and APIs.

You will work with major LLM platforms, optimize prompts, and mentor teams to establish reusable AI frameworks that scale securely with business goals.

Qualifications

• 8+ years of software engineering experience.
• 3+ years delivering enterprise AI solutions.
• Strong Python programming and API development.
• Experience with Azure, AWS or GCP.
• Hands-on with LangChain, LangGraph, CrewAI or Semantic Kernel.
• Strong understanding of LLMs, RAG pipelines, AI agents, embeddings and vector databases.
• Experience with prompt engineering, LLM evaluation and AI optimization.
• Experience integrating AI with enterprise apps, CRM/ERP and APIs.
• Excellent communication, solutioning, stakeholder management and customer-facing consulting skills.

Responsibilities

• Lead customer discovery sessions, translate business requirements into AI-driven solutions.
• Design AI architectures using LLMs, RAG, AI agents, vector databases, and cloud platforms.
• Develop and deploy production-grade AI applications using Python and modern AI frameworks.
• Integrate AI solutions with Salesforce, CRM/ERP systems, APIs, and enterprise data platforms.
• Optimize LLM performance through prompt engineering, RAG optimisation, evaluation frameworks, and feedback loops.
• Work with OpenAI, Claude, Gemini, and other LLM platforms.
• Support PoCs, customer workshops and technical demonstrations.
• Mentor engineering teams and establish reusable AI frameworks and best practices.
• Ensure AI solutions are scalable, reliable, secure, and aligned with business objectives.

Skills

Python

API development

8+ years software engineering

Enterprise AI

LLMs

RAG pipelines

AI agents

Embeddings

Vector databases

Prompt engineering

LLM evaluation

CRM/ERP integration

APIs integration

Tools

Azure

AWS

GCP

LangChain

LangGraph

CrewAI

Semantic Kernel

Job description

Role & responsibilities

• Lead customer discovery sessions, ask probing questions, and translate business requirements into AI-driven solutions.
• Design AI architectures using LLMs, RAG, AI agents, vector databases, and cloud platforms.
• Develop and deploy production-grade AI applications using Python and modern AI frameworks.
• Integrate AI solutions with Salesforce, CRM/ERP systems, APIs, and enterprise data platforms.
• Optimise LLM performance through prompt engineering, RAG optimisation, evaluation frameworks, and feedback loops.
• Work with OpenAI, Claude, Gemini, and other LLM platforms.
• Support technical demonstrations, proof of concepts (PoCs), and customer workshops.
• Mentor engineering teams and establish reusable AI frameworks and best practices.
• Ensure AI solutions are scalable, reliable, secure, and aligned with business objectives.

Preferred candidate profile

• 8+ years of software engineering experience.
• 3+ years of hands-on experience delivering enterprise AI solutions.
• Strong programming skills in Python and experience building APIs.
• Experience with cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform (GCP).
• Hands-on experience with AI frameworks such as LangChain, LangGraph, CrewAI, or Semantic Kernel.
• Strong understanding of LLMs, RAG pipelines, AI agents, embeddings, and vector databases.
• Experience with prompt engineering, LLM evaluation, and AI application optimisation.:
• Experience integrating AI solutions with enterprise applications, CRM/ERP systems, and APIs.
• Excellent communication, solutioning, stakeholder management, and customer-facing consulting skills.

Success Measures

• Deliver scalable AI solutions that demonstrate measurable business value.
• Improve LLM accuracy, reliability, and user adoption.
• Accelerate implementation through reusable AI frameworks and best practices.
• Enable successful enterprise AI deployments and improve customer satisfaction.