Role & responsibilities

- Act as technical SME and collaborate with a team of IT professionals to design, develop and implement Microservices, AI applications
- Define and design enterprise-grade AI/GenAI architectures (LLMs, RAG, Agent systems) with AI-first thinking across product lifecycle
- Fix performance, scalability, and other issues in a very time-critical environment.
- Provide technical guidance to the team for all issues
- Establish reference architectures across AWS, Azure, and GCP including application-layer best practices and reusable AI blueprints
- Provide architectural recommendations and technology roadmaps to client and internal stakeholders
- Define Design patterns, Multi Agent patterns, solution approaches and development guidelines
- Establish benchmarks, standards, techniques, and mechanisms for defining, measuring, and optimizing non-functional requirements.
- Architect solutions using OpenAI, Anthropic, Gemini, Mistral and others popular models
- Design RAG pipelines with optimized retrieval, chunking, embedding tuning, and grounding techniques
- Integrate AI with enterprise systems using API-first, event-driven, and agentic orchestration patterns
- Define AI governance frameworks covering prompt safety, monitoring, bias mitigation, and compliance
- Design pipelines with feedback loops, observability, and continuous learning mechanisms
- Optimize performance including latency, cost, token usage using prompt optimization and caching strategies
- Develop reusable AI accelerators like prompt libraries, SDKs, copilots, utilities
- Lead architecture/ideas reviews and drive AI-first mindset across teams and lifecycle phases




- Lead AI adoption initiatives across the organization by staying current with industry trends and enabling teams through webinars, trainings, and thought leadership content
- Contribute to organization in Design & development of frameworks, tools, accelerators that enhances the ability of technology team members and organization.
- Effort estimating and assist in project planning for the different phases
- Participate in pre-sales providing solutions, and driving technical discussions with client and internal stakeholders

Preferred candidate profile

- 12+ years of experience with strong AI/GenAI architecture background
- Should have commendable expertise in Java, J2EE technologies and frameworks such as Web services, Spring, Python, Databases (Relational & NoSQL, Vector)
- Hands-on experience in Java 17, Multithreading, Concurrency, RESTful web-services, Microservices, Spring Boot, Python, React/Next.js ,NoSQL databases like Mongo
- Experience in AWS is mandatory - S3, IAM, SQS, SNS, Lambda, DynamoDB, CloudWatch, EC2, API Gateway, VPC and other AWS networking basics, security groups, administration basics, vertical and horizontal scaling
- Hands-on experience with LLMs, embeddings, RAG and agent frameworks
- Experience designing and developing AI Agents and Agentic Workflows.
- Experience in any other Cloud Platforms like, Azure, GCP.
- Experience with Azure OpenAI, AWS Bedrock, GCP Vertex AI.
- Experience in LangChain, Semantic Kernel, or similar frameworks




- Good experience in leverage AI Assistants like Claude, Copilot, Cursor.
- Experience in designing migrating existing application to new framework / architecture, redesign, work on POC
- Mandatory experience in building end to end AI solutions by leveraging best models
- Experience in Ecommerce domain (B2B, B2C) is Mandatory.
- Experience ecommerce platforms, CMS, DAM, PIM, OMS, Payment, Loyalty etc.
- Experience integrating AI in enterprise platforms
- Hands-on experience in deploying AI based applications.
- Robust understanding of AI principles
- Experience in evaluating and selecting appropriate AI models and frameworks for enterprise AI use cases.
- Well versed with optimized prompting techniques.
- Experience in working with clients to understand requirements, come up with the product architecture, design and estimate efforts.
- Excellent stakeholder communication and leadership skills
- Experience in Pre-sales (RFP, RFI), propose solutions with focus on portability, modularity, virtualization, cloud adaptation is mandatory
- Must have ability to drive and demand result from team, resolve technical conflicts.
- Experience with Agile software development methodology
- Knowledge about Change and Release management. Should be able to convert requirements to technical solutions
- Should have experience in managing distributed development teams environment (Onshore/Offshore Model)
- Ability to front end big customers / operators with technical and business acumen desirable.
- Active team player & excellent interpersonal interactions skills in a teamwork environment.
- Good communication skills (written, verbal, presentation and listening) and mentoring skills

📌 AI Architect (Noida)
🏢 GSPANN
📍 Noida