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Location: Remote | Job Type: Full-Time | Experience Level: 3+ years
About Us
Cloud202 Limited is a leading technology consulting company dedicated to helping businesses transform and innovate through cutting-edge technology solutions. We specialize in cloud migration, AI/ML, and application development, providing our clients with the expertise they need to stay ahead in a rapidly evolving digital landscape.
Position Overview
We are seeking an innovative AI Engineer to lead the development and implementation of enterprise-grade agentic AI solutions. This role requires deep expertise in the Gen-AI ecosystem, including Amazon Bedrock, Amazon Bedrock Agent Core, Sage Maker AI, and emerging AI agent frameworks. The ideal candidate will drive enterprise AI transformation initiatives and build next-generation intelligent applications using cutting-edge agentic platforms and protocols.
Required Qualifications
Experience
Minimum 3+ years of hands-on experience with AWS cloud services and machine learning infrastructure
2+ years of specific experience with generative AI, large language models (LLMs), and foundation models
Proven track record of building and deploying production-scale AI/ML applications on AWS Certifications Preferred: AWS Certified AI Practitioner or AWS Machine Learning Specialty
Core Technical Skills
Amazon Bedrock Agent Core Platform (Critical)
Agent Core Runtime: Deploy and operate AI agents securely at scale with serverless infrastructure, session isolation, and support for 8-hour execution windows
Agent Core Memory: Implement intelligent session and long-term memory with episodic learning capabilities for context-aware agent interactions
Agent Core Gateway: Build secure, centralized access to tools and APIs with minimal code transformation
Agent Core Identity: Implement seamless agent authentication across AWS services and third-party applications (Slack, Zoom, Git Hub, Salesforce) using OAuth, Okta, Entra, or Amazon Cognito
Agent Core Tools: Utilize Code Interpreter for secure code execution and Browser Tool for enterprise-grade web automation within managed sandbox environments
Agent Core Observability: Implement end-to-end tracing, debugging, and monitoring through unified Cloud Watch dashboards with OTEL compatibility
Agent Core Policy: Set fine-grained boundaries on agent actions with real-time deterministic controls
Agent Core Evaluations: Continuously assess agent quality and behavior for production readiness Gen-AI Services & Foundation Models
Amazon Bedrock: Comprehensive experience with foundation model access, fine-tuning, and deployment
Sage Maker AI: Model hosting, endpoints, auto-scaling, A/B testing, and deployment pipelines
Amazon Q Developer: AI-powered development automation and code transformation capabilities
Foundation Models: Hands-on experience with Claude (Anthropic), Llama (Meta), GPT models (Open AI), Mistral, and Amazon Nova models AI Agents Development & Frameworks
Strands Agents SDK: Build production-ready AI agents with model-driven approach, supporting single agents, multi-agent systems, and swarm architectures
Framework Expertise: Experience with Crew AI, Lang Graph, Llama Index, Google ADK, Open AI Agents SDK, or custom agent frameworks
Multi-Agent Orchestration: Design complex workflows with hierarchical delegation, agent-as-tools patterns, and dynamic capability discovery
Agentic Workflows:



Build autonomous agents that reason, plan, use tools, and maintain context across long-running tasks
Tool Integration: Develop custom tools using Python decorators and integrate external APIs and services Agent Protocols & Interoperability (Essential)
Model Context Protocol (MCP): Implement MCP servers and clients to provide standardized context and tool access to AI agents. Deploy MCP servers in Agent Core Runtime with OAuth authentication
Agent-to-Agent (A2 A) Protocol: Build inter-agent communication systems using A2 A protocol for peer-to-peer agent collaboration, capability negotiation, and task coordination
Agent Discovery: Implement agent cards and capability manifests for dynamic agent discovery and routing
Protocol Integration: Deploy agents supporting both MCP and A2 A protocols for maximum interoperability across enterprise systems Advanced Technical Skills
Vector Databases: Amazon Open Search, Pinecone, or similar for RAG implementations
Programming: Expert-level Python and Java Script/Type Script, with focus on AI/ML libraries and async programming
APIs & Integration: RESTful APIs, Graph QL, JSON-RPC 2.0, Server-Sent Events (SSE), real-time streaming, webhook integration
Prompt Engineering: Advanced prompt flows, few-shot learning, chain-of-thought reasoning, and structured output generation
Knowledge Bases: RAG implementation with enterprise data integration and semantic search
Guardrails & Safety: Bedrock Guardrails, content filtering, bias detection, and responsible AI practices
Custom Model Fine-tuning: Adapting foundation models for domain-specific use cases
Advanced Gen AI Applications
Retrieval-Augmented Generation (RAG): Enterprise search, document Q&A;, knowledge management
Content Generation: Text, image, code, and multimedia content creation
Conversational AI: Chatbots, virtual assistants, customer service automation with memory retention
Code Generation & Analysis: Automated code review, documentation, refactoring, and software modernization
Data Analysis & Insights: Natural language to SQL, automated reporting, business intelligence
Key Responsibilities
Solution Architecture & Design
Design end-to-end generative AI solutions using Amazon Bedrock Agent Core as the primary agentic platform
Architect scalable, cost-effective AI pipelines leveraging Agent Core Runtime for serverless deployment
Implement MCP and A2 A protocols for agent interoperability and tool integration
Design multi-agent architectures with proper orchestration, memory management, and observability
Create technical documentation and best practices for Agent Core implementations Development & Implementation
Build production-ready agentic applications using Amazon Bedrock Agent Core services (Runtime, Memory, Gateway, Identity, Observability)
Develop AI agents using Strands Agents SDK and other framework-agnostic approaches
Implement MCP servers for tool and data access across enterprise systems
Deploy A2 A-compliant agents for cross-platform agent collaboration




Implement RAG systems with vector databases and Agent Core Gateway for secure data access
Create automated workflows for model deployment, monitoring, and evaluation
Integrate AI capabilities into existing enterprise applications with proper authentication and governance Model & Agent Management
Evaluate and select appropriate foundation models for specific use cases
Implement Agent Core Policy for fine-grained control over agent actions and permissions
Use Agent Core Evaluations for continuous quality assessment and optimization
Optimize agent performance, cost, and latency using Agent Core Observability insights
Ensure compliance with data privacy, security requirements, and responsible AI practices Innovation & Research
Stay current with latest AWS AI service releases, Agent Core capabilities, and agentic AI protocols
Experiment with emerging AI techniques, multi-agent patterns, and protocol enhancements
Prototype recent use cases and proof-of-concepts using Agent Core platform
Contribute to internal AI strategy, Agent Core best practices, and community open-source projects Preferred Experience & Skills
Industry-Specific Knowledge
Experience with industry-specific AI applications (healthcare, finance, retail, manufacturing)
Understanding of compliance requirements (GDPR, HIPAA, SOX, PCI-DSS)
Knowledge of AI ethics, bias mitigation, and responsible AI governance Advanced Technical Skills
MLOps: Model lifecycle management, automated retraining, drift detection with Sage Maker Pipelines
Real-time AI: Streaming data processing, low-latency inference, event-driven architectures
Multimodal AI: Text, image, audio, and video processing with Amazon Nova models
Edge AI: Model optimization for edge deployment
Custom Training: Fine-tuning foundation models with proprietary data
Infrastructure as Code: Cloud Formation, AWS CDK, or Terraform for Agent Core deployments Leadership & Collaboration
Experience leading AI transformation initiatives and Agent Core adoption
Ability to communicate complex agentic AI concepts to non-technical stakeholders
Cross-functional collaboration with product, engineering, and business teams
Mentoring junior engineers and data scientists on Agent Core best practices
Recent Technology Awareness
Amazon Bedrock Agent Core GA release with VPC support, A2 A protocol, and enhanced observability
Strands Agents SDK 1.0 with multi-agent orchestration, session management, and A2 A support
Agent-to-Agent (A2 A) protocol under Linux Foundation governance with enterprise adoption
Model Context Protocol (MCP) enhancements for agent-to-agent communication and tool integration
Latest Amazon Nova models (Nova Premier, Nova Sonic) for multimodal and conversational AI
Latest Anthropic Claude models (Claude 4 Sonnet) with extended context and enhanced capabilities
Agent Core Policy and Evaluations for production-grade agent governance
AWS Q Developer CLI integration with MCP for agentic development workflows
Education & Background
Bachelor's degree in Computer Science, AI/ML, Mathematics, or related field
Continuous learning mindset with active participation in AI communities and open-source contributions
Strong understanding of distributed systems, microservices, and serverless architectures
Industry: IT Services and IT Consulting
Employment Type: Full time

Apply on Kit Job: kitjob.in/job/46l6vi

📌 Ai engineer (Vijaypur)
🏢 Cloud202
📍 Vijaypur