AI Architect

GSPANN is hiring an AI Architect to design enterprise-grade AI and GenAI architectures, build cloud reference architectures, and drive AI adoption across the organization.

• Lead as a technical subject-matter expert, collaborating with cross-functional IT teams to design, develop, and implement microservices and AI applications.
• Design enterprise-grade AI and Generative AI (GenAI) architectures, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agent systems, applying AI-first thinking across the product lifecycle.
• Optimize performance and scalability, resolving issues in time-critical environments.
• Support the team with technical guidance across all issues.
• Build reference architectures across Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP), including application-layer best practices and reusable AI blueprints.
• Drive architectural recommendations and technology roadmaps for client and internal stakeholders.
• Develop design patterns, multi-agent patterns, solution approaches, and development guidelines.
• Implement benchmarks, standards, techniques, and mechanisms to define, measure, and optimize non-functional requirements.
• Build solutions using popular models such as OpenAI, Anthropic, Gemini, and Mistral.
• Design RAG pipelines with optimized retrieval, chunking, embedding tuning, and grounding techniques.
• Implement AI integrations with enterprise systems using API-first, event-driven, and agentic orchestration patterns.
• Develop 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, and token usage, through prompt optimization and caching strategies.
• Develop reusable AI accelerators, frameworks, and tools, such as prompt libraries, Software Development Kits (SDKs), copilots, and utilities, that strengthen capabilities across the technology team and the organization.
• Lead architecture and ideation reviews, driving an AI-first mindset across teams and lifecycle phases.
• Drive AI adoption initiatives across the organization by staying current with industry trends and enabling teams through webinars, training, and thought leadership content.
• Support effort estimation and project planning across delivery phases.
• Collaborate in pre-sales activities, proposing solutions and driving technical discussions with client and internal stakeholders.

• Bring a strong AI and GenAI architecture background built over 12+ years.
• Demonstrate expertise in Java, Java 2 Platform Enterprise Edition (J2EE), and frameworks such as web services, Spring, and Python, along with relational, NoSQL, and vector databases.
• Apply hands-on experience with Java 17, multithreading, concurrency, RESTful web services, microservices, Spring Boot, Python, React, Next.js, and NoSQL databases such as MongoDB.
• Work with AWS services including Simple Storage Service (S3), Identity and Access Management (IAM), Simple Queue Service (SQS), Simple Notification Service (SNS), Lambda, DynamoDB, CloudWatch, Elastic Compute Cloud (EC2), API Gateway, and Virtual Private Cloud (VPC), along with core AWS networking, security groups, administration, and vertical and horizontal scaling.
• Apply hands-on experience with LLMs, embeddings, RAG, and agent frameworks.
• Develop AI agents and agentic workflows.
• Work with additional cloud platforms such as Microsoft Azure and GCP.
• Utilize Azure OpenAI, AWS Bedrock, and GCP Vertex AI.
• Apply LangChain, Semantic Kernel, or similar frameworks.
• Utilize AI assistants such as Claude, Copilot, and Cursor.
• Develop migration plans for existing applications to new frameworks or architectures, including redesigns and proof-of-concept (POC) work.
• Bring mandatory experience building end-to-end AI solutions using best-fit models.
• Demonstrate mandatory experience in the ecommerce domain, spanning B2B and B2C.
• Work with ecommerce platforms including Content Management System (CMS), Digital Asset Management (DAM), Product Information Management (PIM), Order Management System (OMS), payment, and loyalty systems.
• Demonstrate proven experience integrating AI capabilities into complex enterprise platform ecosystems.
• Apply hands-on experience deploying AI-based applications.
• Demonstrate a strong understanding of AI principles.
• Apply judgment in evaluating and selecting AI models and frameworks for enterprise use cases.
• Utilize optimized prompting techniques.
• Work with clients to understand requirements, define product architecture, and estimate efforts.
• Bring excellent stakeholder communication and leadership skills.
• Demonstrate mandatory pre-sales experience, including Request for Proposal (RFP) and Request for Information (RFI) processes, proposing solutions focused on portability, modularity, virtualization, and cloud adaptation.
• Manage team performance and resolve technical conflicts to drive results.
• Apply Agile software development methodology.
• Manage change and release processes, and translate business requirements into technical solutions.
• Bring experience managing distributed development teams across onshore and offshore models.
• Demonstrate the ability to front large customer and operator engagements with technical and business acumen, which is an advantage.
• Bring strong interpersonal skills and an active, collaborative team presence.
• Demonstrate strong written, verbal, presentation, listening, and mentoring skills.