Apply on Kit Job: kitjob.in/job/4674x2

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 AgentCore, SageMaker 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 AgentCore Platform (Critical)

- AgentCore Runtime: Deploy and operate AI agents securely at scale with serverless infrastructure, session isolation, and support for 8-hour execution windows
- AgentCore Memory: Implement intelligent session and long-term memory with episodic learning capabilities for context-aware agent interactions
- AgentCore Gateway: Build secure, centralized access to tools and APIs with minimal code transformation
- AgentCore Identity: Implement seamless agent authentication across AWS services and third-party applications (Slack, Zoom, GitHub, Salesforce) using OAuth, Okta, Entra, or Amazon Cognito
- AgentCore Tools: Utilize Code Interpreter for secure code execution and Browser Tool for enterprise-grade web automation within managed sandbox environments
- AgentCore Observability: Implement end-to-end tracing, debugging, and monitoring through unified CloudWatch dashboards with OTEL compatibility
- AgentCore Policy: Set fine-grained boundaries on agent actions with real-time deterministic controls
- AgentCore 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
- SageMaker 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 (OpenAI), 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 CrewAI, LangGraph, LlamaIndex, Google ADK, OpenAI 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 AgentCore Runtime with OAuth authentication
- Agent-to-Agent (A2A) Protocol: Build inter-agent communication systems using A2A protocol for peer-to-peer agent collaboration, capability negotiation, and task coordination
- Agent Discovery: Implement agent cards and capability manifests for agile agent discovery and routing
- Protocol Integration: Deploy agents supporting both MCP and A2A protocols for maximum interoperability across enterprise systems

Advanced Technical Skills

- Vector Databases: Amazon OpenSearch, Pinecone, or similar for RAG implementations
- Programming: Expert-level Python and JavaScript/TypeScript, with focus on AI/ML libraries and async programming
- APIs & Integration: RESTful APIs, GraphQL, 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 GenAI 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 AgentCore as the primary agentic platform
- Architect scalable, cost-effective AI pipelines leveraging AgentCore Runtime for serverless deployment
- Implement MCP and A2A 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 AgentCore implementations

Development & Implementation

- Build production-ready agentic applications using Amazon Bedrock AgentCore 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 A2A-compliant agents for cross-platform agent collaboration




- Implement RAG systems with vector databases and AgentCore 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 AgentCore Policy for fine-grained control over agent actions and permissions
- Use AgentCore Evaluations for continuous quality assessment and optimization
- Optimize agent performance, cost, and latency using AgentCore Observability insights
- Ensure compliance with data privacy, security requirements, and responsible AI practices

Innovation & Research

- Stay current with latest AWS AI service releases, AgentCore capabilities, and agentic AI protocols
- Experiment with emerging AI techniques, multi-agent patterns, and protocol enhancements
- Prototype new use cases and proof-of-concepts using AgentCore platform
- Contribute to internal AI strategy, AgentCore 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 SageMaker 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: CloudFormation, AWS CDK, or Terraform for AgentCore deployments

Leadership & Collaboration

- Experience leading AI transformation initiatives and AgentCore 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 AgentCore best practices

Recent Technology Awareness

- Amazon Bedrock AgentCore GA release with VPC support, A2A protocol, and enhanced observability
- Strands Agents SDK 1.0 with multi-agent orchestration, session management, and A2A support
- Agent-to-Agent (A2A) 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
- AgentCore 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/4674x2

📌 AI Engineer (Nellore)
🏢 Cloud202
📍 Nellore