Position Overview :
We are seeking a skilled Solution Architect specializing in Agentic AI to lead the design, development, and implementation of intelligent autonomous systems. The ideal candidate will bridge the gap between cutting-edge AI research and practical enterprise solutions, architecting robust agentic frameworks that can operate independently while maintaining human oversight and control.
Key Responsibilities :
- Design and architect end-to-end agentic AI solutions that can reason, plan, and execute complex multi-step tasks autonomously
- Develop architectural blueprints for multi-agent systems with proper coordination, communication, and conflict resolution mechanisms
- Create scalable frameworks for agent orchestration, task delegation, and workflow automation
- Design robust memory architectures including episodic, semantic, and procedural memory systems for agents
- Lead cross-functional teams in implementing agentic AI solutions from conception to production deployment
- Establish best practices for agentic system development, testing, and maintenance
- Mentor junior engineers on advanced AI concepts, agent design patterns, and MLOps practices
- Architect and implement LLM deployment strategies for both cloud and on-premise environments
- Design and execute model quantization, pruning, and optimization techniques for efficient inference
- Implement knowledge distillation pipelines to create specialized smaller models from large foundation models
- Develop model versioning, A / B testing, and gradual rollout strategies for production systems
- Design and implement various agentic patterns including ReAct, Chain-of-Thought, Tree-of-Thoughts, and multi-agent collaboration
- Architect tool-using agents with proper API integration, error handling, and safety constraints
- Develop planning and reasoning engines for complex task decomposition and execution
- Implement self-reflection and self-correction mechanisms for autonomous error recovery
Experience & Education :
8+ years of hands-on experience in Machine Learning, Deep Learning, and Data EngineeringBachelor's or Master's degree in Computer Science, AI / ML, Data Science, or related fieldProven track record of deploying ML / AI solutions in production environmentsCore Technical Skills :
Python Expertise : Advanced proficiency in Python with deep understanding of ML libraries (PyTorch, TensorFlow, scikit-learn, Transformers, Hugging Face)Machine Learning & Deep Learning Expertise : Good hands-on experience on training the ML workloads, Fine-Tune the Models, Versioning with A / B TestingCloud Expertise : Must have either of any cloud (Azure / AWS / GCP) Expertise to drive the ML initiativesLLM Mastery : Comprehensive knowledge of Large Language Models including :Foundation models (GPT, Claude, LLaMA, Gemini, etc.)Fine-tuning techniques (LoRA, QLoRA, PEFT methods)Prompt engineering and optimization strategiesModel evaluation and benchmarking methodologiesAgentic AI Specialization
Agent Design Patterns : Hands-on experience implementing :ReAct (Reasoning + Acting) agentsMulti-agent systems and coordination protocolsTool-using agents and API integrationPlanning and goal-oriented agentsConversational and task-oriented agentsMemory & Caching Systems : Deep understanding of :Vector databases and semantic search (Pinecone, Weaviate, Chroma)Memory architectures (short-term, long-term, episodic memory)Caching strategies for LLM inference optimization; Redis CacheContext window management and memory consolidationHuman-in-the-Loop (HITL) Systems : Experience designing :Human oversight and intervention mechanismsApproval workflows and escalation protocolsFeedback collection and model improvement loopsTrust and transparency frameworksDeployment & Infrastructure
Model Deployment : Expertise in :LLM quantization techniques (GPTQ, GGML, AWQ)Model serving frameworks (vLLM, TensorRT-LLM, Triton)Container orchestration (Docker, Kubernetes)Both cloud (AWS / Azure) and on-premise deploymentsAPI Development : Proficiency in :FastAPI framework for high-performance API developmentAsync / await patterns for concurrent processingWebSocket implementations for real-time interactionsAPI security, rate limiting, and monitoringAdvanced Technical Requirements :
Emerging AI Technologies
Experience with multi-modal AI systems (vision-language models, audio processing, video processing)Knowledge of Ethical AI and AI safety techniquesAdvanced Agentic Patterns
Multi-Agent Orchestration : Experience with agent communication protocols, consensus mechanisms, and distributed decision-makingMeta-Learning Agents : Implementation of agents that can learn how to learn and adapt to new tasks quicklyHierarchical Planning : Design of agents with multiple levels of abstraction for complex task executionSelf-Modifying Agents : Understanding of agents that can modify their own code or parametersSoft Skills & Leadership
Communication : Ability to explain complex AI concepts to both technical and non-technical stakeholdersProblem-Solving : Strong analytical and creative problem-solving abilitiesLeadership : Experience leading technical teams and driving architectural decisionsAdaptability : Ability to stay current with rapidly evolving AI landscapeEthics : Strong understanding of AI ethics and responsible AI development practices