Senior GenAI

We are looking for a hands-on Senior AI/GenAI Architect who can own the architecture and technical design of production-grade AI solutions from concept and PoC through development, deployment, and operationalization.

The ideal candidate should have a strong software engineering and architecture foundation, combined with deep hands-on experience in Generative AI, Agentic AI, LLM applications, RAG, AI engineering and AI SDLC.

This is not primarily a delivery/program management or business AI consulting role. We are looking for someone who can demonstrate architectural depth through actual implementations, technical design decisions, code, GitHub/projects, PoCs and production systems.

Key Responsibilities

• Own end-to-end architecture for GenAI and Agentic AI solutions.
• Translate business/technical requirements into scalable, secure and production-ready AI architectures.
• Design and implement:
• LLM-based applications
• RAG architectures
• Agentic workflows
• Multi-agent systems
• Tool/function calling
• Memory and context management
• Human-in-the-loop workflows
• Define architecture across the complete AI SDLC — development, testing, evaluation, deployment, monitoring and continuous improvement.
• Design AI systems that integrate with enterprise applications through APIs, microservices and event-driven architectures.
• Make architectural decisions around:
• Model selection
• RAG vs fine-tuning
• Embeddings/vector databases
• Agent orchestration
• Framework selection
• Cloud/platform selection
• Cost, latency, scalability and performance
• Establish LLMOps/MLOps and AI observability practices including evaluation, tracing, monitoring, quality measurement and feedback loops.
• Define security, governance, Responsible AI and data-protection controls for AI applications.
• Build PoCs/MVPs and reusable frameworks/accelerators to validate architectural decisions.
• Work closely with AI engineers and developers and provide hands-on technical guidance and code-level direction.
• Conduct architecture/design reviews and challenge technical decisions where required.
• Mentor engineers on AI engineering, system design and productionization.

Must-Have Skills

• 12+ years of software engineering / architecture experience.
• Strong hands-on experience in Generative AI / LLM application development.
• Proven experience as an AI Architect / Solution Architect / Technical Architect, not only delivery leadership.
• Strong Python development experience.
• Deep understanding of:
• LLMs
• RAG
• Embeddings
• Vector databases
• Prompt engineering
• Agentic AI
• Agent orchestration
• Tool calling
• AI evaluation
• Hands-on experience with frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, CrewAI or equivalent.
• Strong understanding of system architecture and distributed systems:
• Microservices
• REST APIs
• Event-driven architecture
• Authentication/security
• Scalability
• High availability
• Experience designing production-grade AI applications, not only PoCs or business use-case assessments.
• Experience with AI SDLC / LLMOps, including CI/CD, evaluation, deployment, monitoring and observability.
• Experience integrating AI solutions with enterprise systems and data platforms.
• Strong understanding of cloud AI services such as Azure OpenAI, AWS Bedrock or GCP Vertex AI.
• Ability to create and explain architecture diagrams, technical design documents and architectural trade-offs.

Strongly Preferred

• Experience building reusable GenAI platforms/frameworks, rather than isolated client use cases.
• Experience with:
• MCP
• Multi-agent architecture
• AI coding agents
• Model gateways
• Guardrails
• LLM evaluation frameworks
• Prompt/version management
• AI observability
• Experience implementing GenAI directly into software development workflows / SDLC.
• Active GitHub or demonstrable personal/project work showing actual architecture and implementation depth.
• Experience taking AI solutions from PoC → MVP → production.
• Experience with enterprise security, governance and Responsible AI.