Software Development Director

o Lead end-to-end AWS Process-to-Agent (P2A) transformation programs. o Own overall AWS deployment strategy, execution governance, and delivery assurance. o Define cloud architecture blueprints, standards, and reference frameworks. o Oversee environment setup, landing zones, networking, IAM, security, and compliance controls. o Ensure seamless integration between platform, applications, data, and AI components. o Drive migration, modernization, and cloud-native transformation initiatives. o Review and approve solution architectures before deployment. o Ensure high availability, resilience, scalability, and cost optimization across deployments. o Establish DevSecOps and CI/CD best practices across teams. o Oversee release management, production rollout, and hypercare stabilization.  Agentic AI & Advanced AI Solution Deployment o Lead deployment of Agentic AI solutions on AWS infrastructure. o Architect and oversee implementation of: o Multi-agent systems o RAG-based architectures o Autonomous reasoning and orchestration workflows o LLM-powered enterprise solutions o Ensure secure and scalable deployment of AI models using AWS Bedrock / SageMaker / EKS. o Oversee vector database integration and AI memory systems. o Implement AI observability, guardrails, monitoring, and governance frameworks. o Ensure responsible AI practices, data privacy, and regulatory compliance. o Drive performance optimization and production hardening of AI workloads.  Delivery & Governance Oversight o Own overall AWS deployment deliverables across programs. o Provide technical leadership to architects, DevOps, AI engineers, and platform teams. o Establish deployment governance, risk management, and quality checkpoints. o Conduct architecture reviews and technical audits. o Ensure SLA, SLO, and performance commitments are met. o Drive proactive issue resolution and risk mitigation. o Present deployment status and risk assessments to senior leadership and clients.  Stakeholder & Communication Management o Engage with client executives, CTOs, and business leaders. o Translate business objectives into cloud and AI deployment strategies. o Lead design workshops and executive architecture discussions. o Provide clear communication of technical roadmaps, risks, and deployment milestones. o Mentor senior architects and delivery leaders. o 8+ years of hands-on AWS experience in enterprise environments. o Proven experience leading large-scale AWS production deployments.  EC2, S3, RDS, Aurora, DynamoDB  VPC, Transit Gateway, Direct Connect, Route 53 o Infrastructure as Code: Terraform / CloudFormation / CDK. o CI/CD pipelines and DevSecOps frameworks. o Experience in high-availability and disaster recovery architectures. o Cost optimization and FinOps governance. AI / Agentic AI / GenAI o Experience in Agentic AI architectures (planning agents, reasoning agents, tool usage). o Implementation of:  RAG frameworks  Multi-agent orchestration  Vector databases (FAISS, Pinecone, OpenSearch, pgvector) o Experience with AWS Bedrock / SageMaker for model hosting. o Understanding of embeddings, prompt engineering, and AI evaluation. o Production deployment of AI systems with monitoring and guardrails. o Exposure to hybrid and multi-cloud environments. o Experience with enterprise security and compliance (ISO, SOC2, HIPAA, GDPR). o Experience with Data Engineering pipelines on AWS. o Knowledge of Knowledge Graphs and advanced AI orchestration frameworks. o Prior experience in consulting or client-facing leadership roles. o Ability to define cloud and AI transformation roadmaps. o Strong decision-making capability under ambiguity. o Architecture-first mindset with delivery discipline. o Ability to present to CXO-level stakeholders. o Clear articulation of complex cloud and AI concepts. Execution Focus o Strong governance mindset. o Ability to manage multiple concurrent deployments. o Focus on timelines, quality, and measurable outcomes. o 8+ years of AWS architecture and deployment experience. o 3+ years of hands-on experience in AI/GenAI deployments. o Proven track record of leading enterprise-scale AWS production rollouts. o Bachelor's or Master's degree in Computer Science, Engineering, or related field and minimum 12 to 15 years of relevant experience. o Preferred: AWS DevOps Engineer / AWS ML Specialty.  Lambda, API Gateway  EKS / ECS / Kubernetes  CloudWatch, CloudTrail o Drives quality, resilience, and operational excellence. o Strong risk identification and mitigation capabilities. Communication Excellence