Technical Architect

Tech Architect AWS AI (Anthropic) Experience: - 12+ years of total IT experience, with a minimum of 8 years in AI/ML architecture and solution development. Strong hands-on expertise in designing and building GenAI solutions using AWS services such as Amazon Bedrock, SageMaker, and Anthropic Claude models. Role Overview:- The Tech Architect AWS AI (Anthropic) will be responsible for translating AI solution requirements into scalable and secure AWS-native architectures. This role combines architectural leadership with hands-on technical depth in GenAI model integration, data pipelines, and deployment using Amazon Bedrock and Claude models. The ideal candidate will bridge the gap between strategic AI vision and engineering execution while ensuring alignment with enterprise cloud and security standards. Key Responsibilities: - Design robust, scalable architectures for GenAI use cases using Amazon Bedrock and Anthropic Claude. Lead architectural decisions involving model orchestration, prompt optimization, RAG pipelines, and API integration. Define best practices for implementing AI workflows using SageMaker, Lambda, API Gateway, and Step Functions. Review and validate implementation approaches with tech leads and developers; ensure alignment with architecture blueprints. Contribute to client proposals, solution pitch decks, and technical sections of RFP/RFI responses. Ensure AI solutions meet enterprise requirements for security, privacy, compliance, and performance. Collaborate with cloud infrastructure, data engineering, and DevOps teams to ensure seamless deployment and monitoring. Stay updated on AWS Bedrock advancements, Claude model improvements, and best practices for GenAI governance. Required Skills and Competencies: - Deep hands-on experience with Amazon Bedrock, Claude (Anthropic), Amazon Titan, and embedding-based workflows. Proficient in Python and cloud-native API development; experienced with JSON, RESTful integrations, and serverless orchestration. Strong understanding of SageMaker (model training, tuning, pipelines), real-time inference, and deployment strategies. Knowledge of RAG architectures, vector search (e.g., OpenSearch, Pinecone), and prompt engineering techniques. Expertise in IAM, encryption, access control, and responsible AI principles for secure AI deployments. Ability to create and communicate high-quality architectural diagrams and technical documentation. Desirable Qualifications: AWS Certified Machine Learning Specialty and/or AWS Certified Solutions Architect Professional. Familiarity with LangChain, Haystack, Semantic Kernel in AWS context. Experience with enterprise-grade GenAI use cases such as intelligent search, document summarization, conversational AI, and code copilots. Exposure to integrating third-party model APIs and services available via AWS Marketplace. Soft Skills: Strong articulation and technical storytelling capabilities for client and executive conversations. Proven leadership in cross-functional project environments with globally distributed teams. Analytical mindset with a focus on delivering reliable, maintainable, and performant AI solutions. Self-driven, curious, and continuously exploring innovations in GenAI and AWS services. Our Offering: Global cutting-edge IT projects that shape the future of digital and have a positive impact on environment. Wellbeing programs & work-life balance - integration and passion sharing events. Attractive Salary and Company Initiative Benefits Courses and conferences. Attractive Salary. Hybrid work culture.