AI EngineerCloud202 • Lucknow, IN
AI Engineer
Cloud202 • Lucknow, IN
8 days ago
Job descriptionPreferred : AWS Certified AI Practitioner or AWS Machine Learning Specialty 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 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 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 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 dynamic agent discovery and routing Protocol Integration : Deploy agents supporting both MCP and A2A protocols for maximum interoperability across enterprise systems 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 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 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 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 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 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 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 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 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 Amazon Bedrock AgentCore GA release with VPC support, A2A protocol, and enhanced observability (October 2025) 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 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
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
Core Technical Skills
Amazon Bedrock AgentCore Platform (Critical)
Gen-AI Services & Foundation Models
AI Agents Development & Frameworks
Agent Protocols & Interoperability (Essential)
Advanced Technical Skills
Advanced GenAI Applications
Key Responsibilities
Solution Architecture & Design
Development & Implementation
Model & Agent Management
Innovation & Research
Preferred Experience & Skills
Industry-Specific Knowledge
Advanced Technical Skills
Leadership & Collaboration
Recent Technology Awareness (2025)
Education & Background
Industry : IT Services and IT Consulting
Employment Type : Full-time
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AI Engineer • Lucknow, IN
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