Director - Software Development and Cloud Engineering

Software Development Director

Grade 12 – Software Development Senior Specialist Advisor

Role Description:
We are seeking a highly experienced and strategic technology leader with 15+ years of experience in cloud engineering and enterprise architecture to lead AWS Process-to-Agent(P2A) transformations and Agentic AI solution deployments.
This role will be responsible for end-to-end ownership of AWS cloud deployment deliverables, including architecture governance, execution oversight, solution assurance, operational readiness, and stakeholder communication. The candidate must bring deep real-time experience in large-scale AWS deployments, along with hands-on expertise in AI/GenAI and Agentic AI systems.
This is a leadership role requiring strong communication skills, delivery ownership, architectural authority, and executive-level stakeholder engagement.

Role Responsibilities:
    AWS P2A Deployment Leadership 
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.

Mandatory Technical Skills: 
AWS (Deep Real-Time Deployment Experience Required)
o    8+ years of hands-on AWS experience in enterprise environments.
o    Proven experience leading large-scale AWS production deployments.
o    Strong expertise in:
    EC2, S3, RDS, Aurora, DynamoDB
    VPC, Transit Gateway, Direct Connect, Route 53
    IAM, KMS, Security Hub, GuardDuty
    Lambda, API Gateway
    EKS / ECS / Kubernetes
    CloudWatch, CloudTrail
o    Strong experience designing AWS Landing Zones.
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    Hands-on experience deploying LLM-based enterprise solutions.
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.
Desired Skills
o    Experience managing global cloud transformation programs
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.
Leadership & Behavioral Traits
Strategic Leadership
o    Ability to define cloud and AI transformation roadmaps.
o    Strong decision-making capability under ambiguity.
o    Architecture-first mindset with delivery discipline.
Ownership & Accountability
o    End-to-end accountability for AWS deployment outcomes.
o    Drives quality, resilience, and operational excellence.
o    Strong risk identification and mitigation capabilities.
Communication Excellence
o    Excellent verbal and written communication skills.
o    Ability to present to CXO-level stakeholders.
o    Clear articulation of complex cloud and AI concepts.
o    Strong stakeholder management and influencing skills.
Execution Focus
o    Strong governance mindset.
o    Ability to manage multiple concurrent deployments.
o    Focus on timelines, quality, and measurable outcomes.
Experience requirement:
o    15+ years of overall IT experience.
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.
Educational Qualification 
o    Bachelor’s or Master’s degree in Computer Science, Engineering, or related field and minimum 12 to 15 years of relevant experience.
o    Mandatory: AWS Solutions Architect (Professional preferred).
o    Preferred: AWS DevOps Engineer / AWS ML Specialty.
o    Additional AI/Cloud certifications are an advantage.

Experience Level

Executive Level