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Solutions Architect Agentic AI and Generative AI

Hyderabad, India, Telangana | 2026-11-04

Pranathi Software Services offers great opportunities for career development. Our people are what make us robust. Communication skills and technical expertise are important for our company. Everything we do is centred on teamwork. The staff at our company is open to relocating anywhere in the United States.

At Pranathi Software Services, we offer cutting-edge technology and a commitment to fostering your career.

We offer a competitive benefits package. Learn more about it here.

Together, let's make it happen!

Experience : 10.00 - 20.00 years

Shift Type : 12pm to 9pm

Qualification : Any Degree

Location : Hyderabad, India, Telangana

Mode of Operation : On-site

Number of Openings : 1

Solutions Architect

Agentic AI and Generative AI

Pranathi Software Services

Hyderabad, India | Full-time

About The Role

Pranathi Software Services is seeking a hands-on Solutions Architect to lead the architecture and engineering of our agentic AI and generative AI product portfolio. You will translate product ideas into scalable production systems, establish reusable AI components, and guide engineering teams through implementation.



This role requires strong coding skills and experience delivering AI products beyond proofs of concept.

Our AI Products

- GenZos: Software development automation connecting requirements, architecture, database design, code generation, testing, review, and deployment.

- Digital Employees: AI assistants for sales, support, reception, scheduling, billing, collections, and business operations.

- Voice and Avatar AI: Multilingual AI receptionists, calling assistants, and interactive website avatars.

- Talent Scan: AI phone screening, video interviews, candidate assessment, and interview scheduling.

- Business Applications: AI capabilities across CRM, HRMS, payroll, recruitment, and marketing platforms.

Required Qualifications

- 10 years of software engineering experience, including 3 years in architecture or technical leadership.

- Proven experience delivering production generative AI applications and agentic workflows.

- Strong Python programming skills and working knowledge of TypeScript or JavaScript.

- Experience with LLM APIs, tool calling, structured outputs, streaming, embeddings, and retrieval systems.

- Experience with LangGraph, OpenAI Agents SDK, Semantic Kernel, or comparable frameworks.

- Strong understanding of orchestration, workflow persistence, memory, permissions, and failure recovery.

- Experience with PostgreSQL, vector search or vector databases, Redis, queues, and REST APIs.

- Experience designing secure, multi-tenant SaaS platforms.

- Working knowledge of cloud infrastructure, Docker, CI/CD, automated testing, and observability.

- Strong communication skills and ability to guide engineers through architectural decisions.

- Bachelor’s or master’s degree in Computer Science, Engineering, or a related discipline, or equivalent practical experience.

Preferred Experience

AI coding agents and sandboxed code execution; real-time voice AI and telephony integrations; open-source model deployment and inference optimization; AWS Bedrock, Azure OpenAI, or comparable platforms; CRM, HRMS, ATS, or marketing automation integrations; AI evaluation and cost optimization.

Success Measures

Reliable production deployments; reusable components that accelerate delivery; measurable improvements in task completion, quality, latency, and cost; secure systems with effective monitoring and recovery; and engineering teams able to maintain and extend the architecture.

How to Apply

Share your resume and examples of AI products you have delivered. Highlight your architectural responsibilities, technologies used, production scale, and measurable outcomes.

Roles & Responsibilities

Key Responsibilities





Architecture and Technical Leadership

- Own end-to-end architecture from requirements and prototypes through production deployment.

- Design shared services for model access, orchestration, retrieval, memory, tool execution, evaluation, and monitoring.

- Select models and deployment approaches based on quality, latency, privacy, and operating cost.

- Define boundaries between application logic, autonomous actions, and decisions requiring human approval.

- Create technical specifications, architecture diagrams, implementation plans, and engineering standards.

- Review critical code, troubleshoot complex issues, and mentor AI and full-stack engineers.

Agentic AI and Generative AI

- Design single-agent and multi-agent workflows for planning, delegation, execution, validation, and recovery.

- Implement persistent state, checkpoints, retries, timeouts, and human intervention.

- Build secure integrations using APIs, function calling, MCP, and application connectors.

- Architect RAG pipelines covering document ingestion, embeddings, vector search, reranking, and source attribution.

- Implement structured outputs, schema validation, context management, memory, and model routing.

- Control agent loops, duplicate actions, token usage, and unauthorized tool execution.

Product Architecture and Production Delivery

- GenZos: Design coordinated development agents and secure, isolated environments for generated code execution, testing, repository integration, and controlled deployment.

- Digital Employees: Build business workflows with application integrations, approval steps, escalation, and human handoff.

- Voice and Avatar AI: Integrate speech recognition, LLMs, speech synthesis, interruption handling, and business tools for real-time multilingual conversations.

- Talent Scan: Design screening and interview workflows with consistent assessment criteria, supporting evidence, and human review.

- Business Applications: Integrate tenant-aware AI workflows with appropriate permissions and audit trails.

- Establish evaluation datasets and release criteria for response quality, task completion, grounding, tool accuracy, latency, and cost.

- Implement tracing and monitoring across model calls, retrieval, tools, and agent workflows.

- Address prompt injection, sensitive data exposure, unsafe code execution, and cross-tenant data leakage.

- Design fallback behavior, usage limits, recovery procedures, and graceful handling of model or tool failures.

Partner with product owners and technical project managers to estimate effort, manage dependencies, and deliver milestones

Required Key Skills python, architectural leadership, software engineering, llm apis, cloud infrastructure

Apply Now

Years of Experience * Below 1 Year 1 Year 2 Year 3 Year 4 Year 5 Year 6 Year 7 Year 8 Year 9 Year 10 Year 11 Year 12 Year 13 Year 14 Year 15 Year 16 Year 17 Year 18 Year 19 Year Above 20 Year

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📌 Solutions Architect Agentic AI and Generative AI (Hyderabad)
🏢 Pranathi Software Services
📍 Hyderabad