Applied AI Architect

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Python, TensorFlow, AWS and cloud side

We are seeking an experienced AI Architect with 12–15 years of software development experience and a proven track record in leading AI/ML initiatives. This role demands hands-on expertise in deploying AI/ML models at scale, proficiency in Generative AI frameworks, and an in-depth understanding of cloud platforms and modern software technologies. The candidate should demonstrate strong business acumen, excellent communication skills, and the ability to design innovative, scalable solutions that align with organizational goals.

• 12 – 15 years of experience in software development. **Not looking for 18+ years of experience, Max experience should be 15 – 16 years.**

Key Responsibilities:

Agentic AI, Autonomous Workflow Design and Data Pipelines

• Architect and deploy agentic AI systems using CrewAI, LangChain, and LangGraph to automate complex enterprise workflows.
• Design multi-agent orchestration strategies with memory, tool usage, and inter-agent communication using fast evolving industry standards like MCP and A2A.
• Implement guardrails, safety layers, and fallback mechanisms to ensure reliability and trust in autonomous agents with focus on human in the loop.

RAG & LLM Integration

• Build Retrieval-Augmented Generation (RAG) pipelines using vector databases (e.g., FAISS, Pinecone, Weaviate) and semantic search.
• Optimize LLM performance through prompt tuning, context compression, and hybrid retrieval strategies.
• Ensure modularity and extensibility of RAG components for reuse across business domains.
• Design scalable data platforms supporting structured, semi-structured, and unstructured data for AI workloads.
• Preferred knowledge of Integrate AI capabilities with TIBCO’s enterprise stack (Spotfire, EBX, Data Virtualization).
• Lead implementation of MLOps, LLMOps, and AI observability frameworks for model lifecycle management.

FinOps & Cost Optimization

• Implement FinOps practices to monitor and optimize cloud and AI infrastructure costs.
• Establish cost governance models, usage-based budgeting, and forecasting for GenAI workloads.
• Use tools like CloudHealth, Kubecost, or custom dashboards to drive cost transparency and accountability.

Security, Governance & Compliance

• Define and enforce AI governance frameworks including model risk management, bias mitigation, and ethical AI.
• Ensure compliance with global data privacy regulations, AI ACTs and internal security policies.
• Conduct architecture reviews, threat modeling, and secure deployment strategies for AI agents and data pipelines.

Strategic Leadership & Enablement

• Act as a trusted advisor to business and technology stakeholders, translating AI capabilities into business value.
• Mentor cross-functional teams on agentic design patterns, data engineering, and platform scalability.
• Develop reusable reference architectures, accelerators, and playbooks to scale AI adoption across the enterprise.

Required Qualifications:

• 10+ years in enterprise architecture with 5+ years in AI/ML, data platforms, and cloud-native environments. 1+ years in Agentic AI, GenAI solutions.
• 15+ years of overall IT experience in building and architecting enterprise grade solutions.
• Proven experience with GenAI, LLMs, agentic frameworks (CrewAI, LangChain, LangGraph), and RAG architectures.
• Strong understanding of FinOps, cloud cost modeling, and optimization strategies.
• Deep expertise in MLOps, LLMOps, containerization (Docker, Kubernetes), and CI/CD pipelines.
• Excellent communication, stakeholder engagement, and leadership skills.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Information Technology

• Industries

  IT Services and IT Consulting

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