Principal Engineer

SourcingXPress; Hyderabad; On-site; INR 3,500,000 - 4,500,000; Full time

Job summary

People Impact in Hyderabad is seeking an experienced Java Solution Architect to design and govern scalable, secure cloud-native enterprise architectures. The role requires hands-on leadership in Java and Spring, with AI-Native patterns including RAG, LLMs, and agentic frameworks, and collaboration with engineering, QE, DevOps, and client teams.

You will drive architectural standards, codify High-Level and Low-Level designs, and mentor teams while ensuring security, scalability, and compliance

Qualifications

• 9+ years of overall software engineering experience, with 13+ years preferred.
• 3–5+ years in a Solution/Technical Architect role, designing both on-premises and cloud-based systems.
• Expert-level knowledge of Java, Spring Boot, REST APIs, Spring Batch.
• Strong experience in microservices architecture and distributed systems.
• 3+ years hands-on AI-Native architecture including RAG, LLMs, embeddings, agentic frameworks, GenAI integrations, memory management, cloud AI services.
• Hands-on with Azure OpenAI, GenAI solution development, and LLM fine-tuning or customization.
• Good HLD/LLD, design patterns, and technical documentation.
• DevOps tools: Maven, Git, CI/CD, and Autosys.
• Understanding of cloud architecture, security, scalability, and deployment models.
• Excellent communication and stakeholder-management skills.

Responsibilities

• Design and own scalable, resilient, and cloud-native architectures for enterprise Java platforms.
• Define and document HLD and LLD for complex systems.
• Lead architecture reviews and technical design discussions across squads.
• Enforce coding standards, architectural best practices, and engineering principles.
• Provide technical leadership and mentorship to development and QE teams.
• Collaborate with client and partner teams to drive milestones.
• Design and implement AI-Native architectures using RAG, embeddings, LLMs, and agentic frameworks.
• Leverage Azure AI and Azure OpenAI for GenAI solutions.
• Drive DevOps automation, CI/CD, and deployment practices.
• Ensure security, scalability, reliability, and compliance with enterprise requirements.

Skills

Java

Spring Boot

REST APIs

Spring Batch

Microservices

AI‑Native architecture

LLMs

RAG

Embeddings

Azure OpenAI

DevOps

Tools

Maven

Git

CI/CD

Autosys

Job description

Job Description

Company: People Impact

LinkedIn: Visit LinkedIn

Business Type: Startup

Company Type: Service

Business Model: B2B

Funding Stage: Pre-seed

Industry: Fintech

Salary Range: ₹ 35-45 Lacs PA

We are seeking an experienced Java Solution Architect to design, define, and govern scalable, secure, and cloud-native enterprise architectures.

The ideal candidate will have strong expertise in Java and Spring technologies, proven architectural leadership, and hands‑on experience with AI‑Native architecture patterns, including RAG, LLMs, Agentic AI frameworks, and cloud-based AI services.

The role will involve working closely with engineering, QE, DevOps, and client teams to drive technical strategy, architecture standards, and successful delivery of enterprise solutions.

Key Responsibilities

• Design and own scalable, resilient, and cloud-native application architectures for enterprise Java platforms.
• Define and document High-Level Design (HLD) and Low-Level Design (LLD) for complex systems and applications.
• Lead architecture reviews, technical design discussions, and code reviews across development squads.
• Establish and enforce coding standards, architectural best practices, design patterns, and engineering principles.
• Provide technical leadership, mentorship, and guidance to development and QE teams.
• Collaborate with onshore client and partner teams to understand requirements, align priorities, and drive project milestones.
• Design and implement AI-Native architectures leveraging:
• Retrieval-Augmented Generation (RAG)
• Embeddings and vector-based retrieval
• LLM integrations and deployments
• Agentic AI frameworks
• AI application memory management strategies
• Leverage Azure AI and Azure OpenAI services for enterprise GenAI solutions and deployment.
• Define strategies for memory management, context handling, and knowledge retrieval in AI-powered applications.
• Drive DevOps automation, CI/CD, and deployment practices across application teams.
• Work closely with security, infrastructure, and platform teams to ensure solutions meet enterprise security, scalability, reliability, and compliance requirements.
• Provide technical direction across multiple squads and contribute to organization-wide architecture initiatives.

Required Skills & Experience

• 9+ years of overall software engineering experience, with 13+ years preferred.
• 3–5+ years of experience in a Solution/Technical Architect role, designing both on-premises and cloud-based systems.
• Expert-level knowledge of:
• Java
• Spring Boot
• REST APIs
• Spring Batch
• Strong experience in microservices architecture, distributed systems, and enterprise application design.
• 3+ years of hands‑on experience with AI‑Native architecture, including:
• RAG
• LLMs
• Embeddings
• Agentic frameworks
• GenAI integrations
• AI application memory management
• Cloud AI services
• Hands‑on experience with Azure OpenAI, GenAI solution development, and LLM/model fine‑tuning or customization.
• Strong understanding of HLD/LLD, architecture patterns, design principles, and technical documentation.
• Experience with DevOps and engineering tools, including Maven, Git, CI/CD, and Autosys.
• Good understanding of cloud architecture, security, scalability, and deployment models.
• Good to have experience with RPM packaging and Linux environments.
• Excellent communication and stakeholder‑management skills, with the ability to interact effectively with both technical and non-technical stakeholders.
• Ability to act as a Subject Matter Expert (SME) across multiple IS disciplines, including business solutions, systems development, security, and technology architecture.

Preferred Profile

• Candidates with strong AI‑Native Solution Architecture experience will be highly preferred, particularly those who have hands‑on expertise in RAG, LLMs, Agentic AI frameworks, Azure OpenAI, embeddings, and enterprise GenAI solutions.
• The ideal candidate should combine deep Java architecture expertise with modern AI and cloud capabilities and be comfortable driving technical decisions across large, complex enterprise environments.