Technical Architect (DevOps)

Cloud Strategy & Architecture: Define and execute the bank’s Azure and AWS strategy, target architecture, landing zones, account/subscription model, guardrails, shared services, and migration roadmap. Design secure, resilient, scalable, and cost-effective hybrid and multi-cloud solutions across compute, storage, networking, databases, integration, identity, containers, and serverless services. Lead workload assessments and select appropriate rehost, replatform, refactor, retire, retain, or replace strategies. Establish reusable architecture patterns, golden paths, reference implementations, policy-as-code, and technical standards for regulated workloads. Conduct architecture reviews and ensure alignment with enterprise architecture, security, data, operational resilience, and regulatory requirements. Infrastructure, Operations & Resilience: Own the strategic direction for hybrid infrastructure, including network, compute, storage, virtualization, identity, backup, database platforms, middleware, end-user dependencies, and data-center integrations. Improve operational maturity across incident, problem, change, release, capacity, availability, configuration, patch, vulnerability, backup, and service-continuity management. Define service-level objectives, reliability indicators, error budgets, recovery objectives, operational readiness criteria, escalation paths, and executive service reporting. Lead major incident response, root-cause analysis, corrective actions, resilience testing, disaster-recovery exercises, and systemic risk reduction. Implement end-to-end observability, event correlation, actionable alerting, service mapping, capacity forecasting, and automated remediation. Drive simplification, standardization, technical-debt reduction, lifecycle management, platform currency, and retirement of unsupported technologies. DevOps, Platform Engineering & Automation Champion a DevOps engineering culture based on shared ownership, secure automation, continuous improvement, rapid feedback, and frequent low-risk releases. Design and govern CI/CD and GitOps practices using Azure DevOps, GitHub Actions, GitLab CI, Jenkins, or equivalent enterprise tooling. Drive Infrastructure as Code and configuration automation using Terraform, Bicep/ARM, CloudFormation, Ansible, PowerShell, Python, or Bash. Lead container and orchestration adEligible to workion using Docker, Kubernetes, AKS, EKS, and related platform services. Embed automated testing, code quality, secrets management, vulnerability scanning, artifact controls, policy checks, segregation of duties, and deployment approvals into pipelines. Track engineering outcomes through deployment frequency, lead time for change, change failure rate, recovery time, availability, automation coverage, platform adEligible to workion, and technical-debt reduction. AI Integration & Intelligent Operations - Preferred: Identify and prioritize responsible AI, generative AI, and machine-learning opportunities across IT operations, engineering productivity, service management, knowledge management, fraud/risk support, and customer or employee experiences. Integrate AI capabilities using services such as Azure AI Foundry/Azure OpenAI, Azure Machine Learning, Amazon Bedrock, Amazon SageMaker, or comparable enterprise platforms. Support MLOps and GenAIOps practices, including model and prompt versioning, automated pipe lines, evaluation, deployment, observability, drift detection, grounding, rollback, and lifecycle controls. Apply secure and responsible AI principles covering privacy, data lineage, access control, human oversight, output validation, explainability, model risk, prompt-injection defense, and confidential-data protection. Evaluate AIOps use cases for anomaly detection, predictive incident management, alert reduction, root-cause analysis, capacity forecasting, and self-healing operations. Partner with data, cybersecurity, legal, compliance, model-risk, and business teams to move AI proofs of value into governed, production-ready services. Security, Risk, Compliance & FinOps: Partner with cybersecurity, enterprise architecture, operational risk, audit, compliance, data governance, and model-risk teams to implement controls aligned with bank policy and applicable regulatory expectations. Apply zero-trust, least-privilege, segregation-of-duties, encryption, key management, privileged-access, secure configuration, immutable logging, and continuous-monitoring principles. Maintain evidence-ready controls and support risk assessments, technology control testing, audits, remediation plans, regulatory examinations, and third-party reviews. Implement FinOps practices for budgeting, tagging, showback/chargeback, commitment management, rightsizing, waste reduction, licensing Eligible to workimization, and unit-cost transparency. Manage vendor performance, statements of work, service levels, architectural compliance, delivery risks, commercial outcomes, and knowledge transfer. Disclaimer: Diverse Lynx LLC is an Equal Opportunity Employer. All applicants and employees are evaluated without discrimination, based solely on their qualifications, ability, competence and performance. This email and its attachments may contain confidential or proprietary information and is intended only for the recipient(s). If you received this message in error, please disregard it and notify the sender. If you no longer wish to receive our communications, you may at any time. 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Havey Azure, DevOps with AwS Exp. Must Have Technical/Functional Skills: 6-7 years’ experience across cloud, infrastructure engineering, production operations, platform engineering, SRE, DevOps, or enterprise technology transformation. At least 1-2 years in architecture, program ownership, or technology partner roles with accountability for critical platforms, budgets, vendors, regulatory commitments, and distributed teams. Strong expertise across Microsoft Azure and AWS, including enterprise landing zones, identity, networking, compute, storage, databases, containers, security, observability, resilience, governance, and cost management. Preferred DevOps engineering background with credible hands-on experience in CI/CD, GitOps, Infrastructure as Code, automation, scripting, containers, orchestration, observability, release engineering, and production support. Proven leadership of cloud adEligible to workion, data-center modernization, hybrid-cloud transformation, migration, platform engineering, resilience, automation, technical-debt reduction, or operating-model change. Deep knowledge of network and infrastructure architecture, identity and access management, backup and recovery, capacity, performance, virtualization, middleware, databases, patching, vulnerability management, and lifecycle governance. Demonstrated command of incident, problem, change, release, availability, configuration, continuity, disaster recovery, major-incident, and service-level management. Strong understanding of DevSecOps, zero trust, cloud security controls, operational resilience, audit evidence, technology risk, compliance, and third-party governance in banking or financial services. Excellent executive communication, stakeholder influence, vendor and commercial management, negotiation, financial management, facilitation, and organizational leadership skills. Ability to work onsite as required, lead across time zones, and provide executive and technical direction during critical incidents or planned changes. Significant experience in banking, financial services, payments, lending, deposits, risk, treasury, digital banking, or another highly regulated and high-availability environment. Demonstrated delivery of enterprise AI/ML, generative AI, agentic AI, AIOps, MLOps, or AI-enabled engineering and operations initiatives. Experience integrating Azure AI Foundry/Azure OpenAI, Azure Machine Learning, Amazon Bedrock, Amazon SageMaker, or comparable enterprise AI services into secure platforms and operating workflows. Knowledge of responsible AI, model governance, data privacy, AI evaluation, retrieval-augmented generation, prompt and model lifecycle management, human oversight, and production AI monitoring. Experience applying AI to anomaly detection, predictive incident management, event correlation, root-cause analysis, capacity forecasting, operational knowledge, engineering productivity, and automated remediation. Relevant certifications such as Azure Solutions Architect Expert, Azure DevOps Engineer Expert, AWS Solutions Architect Professional, AWS DevOps Engineer Professional, Kubernetes, Terraform, ITIL, SRE, FinOps, or cloud security credentials. Experience with ServiceNow, Splunk, Dynatrace, AppDynamics, Grafana, Prometheus, Azure Monitor, Amazon CloudWatch, OpenTelemetry, or comparable observability and service-management platforms. Experience establishing internal developer platforms, cloud centers of excellence, reusable engineering patterns, service catalogs, golden paths, and communities of practice.