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Principal Solution Architect - Presales
A PE backed , fast growing AI first product engineering firm
Principal Solution Architect - Presales

Principal Solution Architect - Presales at A PE backed , fast growing AI first product engineering firm · Pune · 15 - 20 years · ₹45L - ₹60L / yr · Posted 16 Sep 2026

Intellikart Ventures LLP's logo

Principal Solution Architect - Presales

at A PE backed , fast growing AI first product engineering firm

15 - 20 yrs
₹45L - ₹60L / yr
Pune
Skills
Presales
Solution architecture
Solution selling
Technology integration
Artificial Intelligence (AI)
Product engineering

Overview:

We are looking for a Principal Architect for a Private Equity backed, fast growing AI First Product Engineering Services firm.

This role will be a key member of the core leadership team of the firm.


He/ She will serve as a strategic technical leader, solution designer, and customer advisor. In this role, you will combine deep and broad-based technical expertise with strong business acumen to architect high-value solutions, lead pre-sales engagements, and mentor our practice/CoE team. You will work closely with customers to understand their business needs, translate them into scalable technical solutions, and guide delivery teams in successful implementation.


Responsibilities:

1. Solutioning & Pre-Sales

●     Engage with customers, understand their business context, and guide them through a discovery and design process leading to a proposed solution

●     Work with sales teams to develop winning proposals, RFP responses, and technical presentations.

●     Will need to take single point ownership of the pre sales process, including client interactions, proposal preparation, presentations, pricing etc

●     Drive proof-of-concepts as part of the pre sales process

●     Build frameworks for different kinds of proposals and presentations to bring in repeatability and efficiency in the process

●     Work closely with marketing to create content around Indexnine offerings, solutions, capabilities and case studies

 

2. Delivery

 

●     Provide technical oversight during project delivery, ensuring adherence to architectural principles, standards, and best practices and ensure the as-sold solution is realised

●     Act as a trusted advisor to senior customer stakeholders (CXO level and technical leads). Will need to engage with Customers through delivery as required

●     Create points of view on accounts to help mine and grow accounts.

 

3. Practice & CoE Development

 

●     Work closely with the labs. Contribute to the development of new products/ accelerators.

●     Mentor and coach engineers to enhance their technical and customer engagement skills.

 

 

 

4. Thought leadership

●     Keep abreast of technology and produce points of view for Indexnine’s offerings and technical capabilities

●     Represent the company at industry forums, webinars, and client workshops.

●     Be able to independently conduct discovery and solutioning workshops with Customers

 

 

Skills/Qualifications:

●     15+ years of overall experience with a blend of architecting, pre sales and technical delivery

●     Should be leading a pre-sales unit in a services organization. Hands-on with designing solutions, proposal writing, estimation, pricing and customer presentations.

●     Broad based technical expertise and having played a Sr Architect role for at least 2 years

●     Excellent communication, stakeholder management, and team leadership skills.

●     Experience working in an IT services environment in the Product Engineering space (i.e designing and building bespoke products/solutions)

●     BE/ Masters degree

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  • Select appropriate AI models and platforms based on quality, latency, cost, security, and operational requirements.
  • Design cloud-native architectures, APIs, integrations, identity controls, monitoring, and resilient deployment patterns.
  • Create architecture diagrams, technical designs, implementation roadmaps, and technical standards.
  • Implement AI quality and safety measures, including hallucination mitigation, guardrails, access controls, and prompt-injection defenses.
  • Guide engineering, data, ML, and DevOps teams through implementation, code reviews, troubleshooting, and go-live readiness.
  • Lead technical discussions and design reviews with US client stakeholders.
  • Establish production monitoring, CI/CD, versioning, incident handling, and performance and cost optimization practices.


Required Skills & Qualifications

  • 8+ years of relevant experience in software engineering, AI/ML engineering, data engineering, or technology architecture.
  • Proven experience personally architecting and deploying at least one enterprise-grade AI or Generative AI solution into production.
  • Strong practical knowledge of LLMs, RAG, embeddings, vector databases, orchestration frameworks, and model evaluation.
  • Hands-on experience with Python and APIs, including prototyping, code review, and troubleshooting.
  • Experience with at least one major cloud platform: Microsoft Azure, AWS, or Google Cloud Platform (GCP).
  • Understanding of data pipelines, SQL/NoSQL databases, containers, CI/CD, MLOps, and LLMOps.
  • Knowledge of enterprise security, privacy, identity and access management, and responsible AI practices.
  • Experience independently leading architecture workshops, design reviews, and technical discussions with US clients.
  • Excellent written and spoken English, documentation, and stakeholder management skills.
  • Availability to work from 3:00 PM to 12:00 AM IST and willingness to accept a contractual engagement.


Preferred Experience

  • Azure AI Foundry, Azure OpenAI, Amazon Bedrock, or Google Vertex AI.
  • Azure AI Search or equivalent retrieval tools.
  • LangChain, LangGraph, Semantic Kernel, and agent/tool orchestration.
  • Model fine-tuning, predictive ML, document intelligence, multimodal AI, or real-time AI applications.
  • Experience in cloud modernization, enterprise integrations, data analytics, or technology consulting.
  • Relevant AI/cloud architecture certifications and experience mentoring technical teams.


What Success Looks Like

  • Designing secure, scalable, production-ready AI solutions rather than demos or conceptual presentations.
  • Making sound technical decisions around feasibility, performance, reliability, cost, and AI risks.
  • Taking ownership of architecture decisions and resolving technical blockers with limited supervision.
  • Building trust with senior US stakeholders and collaborating effectively with India-based delivery teams.


Contract Details

  • Initial engagement: Minimum 3 months, with extension subject to project requirements and performance.
  • Working schedule: 3:00 PM – 12:00 AM IST.
  • Potential permanent employment: After 18 months, the client may consider direct permanent employment at its sole discretion. Conversion is not guaranteed.


Mandatory Screening Criteria


Candidates should be able to:

  • Explain an enterprise AI/GenAI solution they personally architected and deployed, including architecture, scale, evaluation, and business impact.
  • Whiteboard an enterprise RAG or agentic solution covering data flow, security, authentication, authorization, monitoring, and cost controls.
  • Discuss real-world model-quality issues, hallucinations, privacy risks, incidents, and architectural trade-offs.
  • Lead a technical design review with US client stakeholders.
  • Confirm acceptance of the working hours and contractual engagement.


Apply only if you have hands-on experience architecting and deploying enterprise AI/GenAI solutions in production.


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Shubham Vishwakarma

Full Stack Developer - Averlon
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