2 days ago
Hyderābād, IndiaStaff+
Responsibilities
- Architect and implement agentic GenAI systems using modern LLM orchestration frameworks.
- Design multi-agent architectures, including planner–solver patterns, hierarchical agents, autonomous teams, and goal decomposition workflows.
- Define end-to-end GenAI architecture spanning model selection, orchestration, memory, tools, security, observability, and deployment.
- Build reusable agent tooling, APIs, and memory architectures for coordination, context persistence, and scalable interaction.
- Lead hands-on development and production deployment of assistants, copilots, workflow automation, and decision-support systems.
- Evaluate, integrate, and optimize LLMs, multimodal models, and RAG pipelines using vector databases and retrieval systems.
- Optimize systems for performance, reliability, scalability, cost efficiency, and responsible AI constraints.
- Establish and enforce GenAIOps and LLMOps practices, including evaluation, monitoring, logging, feedback loops, and continuous improvement.
- Guide and mentor teams on agent design patterns, prompt engineering, tool abstraction, fine-tuning, and best practices.
- Translate business requirements into scalable agent-based solutions and AI roadmaps with product, business, and domain stakeholders.
- Drive technology strategy and innovation by tracking advances in multi-agent systems, cognitive architectures, and open-source AI frameworks.
Requirements
- 10+ years of experience.
- Hands-on experience architecting and implementing agentic GenAI systems and multi-agent workflows.
- Experience with LLM orchestration, model selection, RAG pipelines, vector databases, memory architectures, tools, APIs, and production deployment.
- Experience evaluating and optimizing LLMs and multimodal models, including OpenAI, Claude, Gemini, Mistral, and LLaMA.
- Knowledge of GenAIOps/LLMOps practices, observability, evaluation, monitoring, logging, feedback loops, and continuous improvement.
- Experience with prompt engineering, tool abstraction, fine-tuning, security, privacy, scalability, reliability, and responsible AI.
- Ability to lead technical strategy, mentor teams, and collaborate with product, business, and domain stakeholders.