devops architect

Integrant

<div>We are seeking an exceptional Senior Lead who combines deep hands-on SysOps/HPC expertise with the strategic vision of a solution architect. This is a rare dual-track role: you operate at the intersection of elite technical execution and client-facing presales, designing and running mission-critical GPU, HPC, and Kubernetes platforms while simultaneously co-creating opportunity with our commercial teams. 
This role carries both SysOps, HPC depth and DevOps. You are expected to spend at least 60% of your time on implementation and technical execution
What You Will Do
Presales &amp; Business Development<ul><li>Partner with sales and solution teams to identify and qualify new opportunities</li><li>Lead or support technical presales activities: discovery workshops, RFP responses, architecture presentations</li><li>Build and deliver proof-of-concepts (POCs) that demonstrate platform capabilities to prospective clients</li><li>Prepare high-quality technical materials</li><li>Act as a trusted technical advisor during client conversations, proposing solutions aligned to business goals</li></ul> 
In-Account Delivery &mdash; SysOps &amp; DevOps Execution<ul><li>Operate directly within client accounts as a senior SysOps/DevOps engineer
</li><li>Run, troubleshoot, and optimize production-grade Kubernetes clusters and GPU/HPC environments hands-on</li><li>Own Linux system administration at a deep level: kernel tuning, storage, networking, performance profiling</li><li>Implement and maintain IaC pipelines, GitOps workflows, and CI/CD systems</li><li>Serve as the senior escalation point for complex operational incidents within accounts</li></ul> 
Architecture &amp; Solution Design<ul><li>Design end-to-end platform architectures spanning cloud, hybrid, and on-premises HPC environments</li><li>Define workload isolation models, networking architectures, and storage strategies for multi-tenant platforms</li><li>Recommend and validate technology choices aligned to client scale, budget, and team maturity</li><li>Produce architecture decision records (ADRs), solution blueprints, and technical runbooks</li></ul>
Technical Competencies &amp; Requirements
1. Architecture &amp; System Design<ul><li>Design production-grade multi-cluster Kubernetes platforms:</li><li>RKE2, EKS (AWS), AKS (Azure) at enterprise scale</li><li>GPU-aware clusters: NVIDIA H100 / A100 / B200 node pools</li><li>Hybrid cloud + on-premises HPC infrastructure</li><li>Define and document:</li><li>Workload isolation: namespaces, MIG partitioning, multi-tenancy models</li><li>Networking: BGP peering, Ingress controllers, service mesh (Istio / Cilium)</li><li>Storage: Longhorn, Ceph, distributed and high-throughput file systems</li></ul> 
2. Platform Engineering &amp; GitOps Strategy<ul><li>Define and enforce platform standards across the delivery lifecycle</li><li>GitOps tooling: ArgoCD, Fleet &mdash; declarative cluster management</li><li>CI/CD pipelines: Azure DevOps, Jenkins &mdash; build, test, promote</li><li>Infrastructure as Code: Terraform (modules, remote state, workspaces), Ansible</li><li>Standardize cluster bootstrapping, app deployment lifecycle, environment promotion (Dev QA Prod)</li></ul> 
3. AI / GPU Infrastructure Architecture (Priority Competency)<ul><li>Design and operate GPU compute platforms at scale:</li><li>GPU Operator deployment and lifecycle management</li><li>MIG (Multi-Instance GPU) partitioning for multi-tenant workloads</li><li>Advanced scheduling: Run:AI, Kubernetes-native GPU scheduling (device plugins)</li><li>Understand AI workload classes and their infrastructure implications:</li><li>Distributed training workloads (data/model/pipeline parallelism)</li><li>Inference pipelines &mdash; NVIDIA Triton Inference Server, TensorRT optimization</li><li>Align infrastructure to the full AI stack:</li><li>CUDA stack, cuDNN, NCCL collective communication libraries</li><li>High-speed networking: InfiniBand (HDR/NDR), RoCE for RDMA</li><li>GPUDirect RDMA / GPUDirect Storage for low-latency data paths</li></ul> 
4. Observability &amp; Reliability Engineering<ul><li>Define and implement full-stack observability:</li><li>Metrics: Prometheus, Thanos (long-term retention, multi-cluster)</li><li>Logs: Loki, Fluent Bit</li><li>GPU telemetry: DCGM Exporter, NVIDIA Nsight Systems</li><li>Build operational frameworks:</li><li>SLO / SLA definitions and error budget tracking</li><li>Alerting strategy &mdash; noise reduction, severity routing</li><li>Incident response playbooks and on-call runbooks</li></ul> 
5. Security &amp; Multi-Tenancy Architecture<ul><li>Design zero-trust security postures for multi-tenant platforms</li><li>Secret management: HashiCorp Vault, External Secrets Operator</li><li>Identity and access: IAM, RBAC, SSO/OIDC integration</li><li>Network isolation: NetworkPolicy, micro-segmentation, mTLS</li><li>Secure GPU sharing: MIG isolation, VGPU licensing, tenant boundary enforcement</li></ul> 
6. HPC, Data &amp; Storage Architecture (Priority Competency)<ul><li>Understand the high-performance storage for AI/HPC workloads:</li><li>GPUDirect Storage &mdash; bypassing CPU for GPU-native I/O</li><li>Distributed file systems: Weka (high-throughput NFS/S3), Ceph (scalable object/block)</li><li>Storage tiering, caching strategies, and data lifecycle management</li><li>Size and validate storage architectures against workload I/O profiles</li></ul> 
7. Operational Leadership &amp; Linux Systems<ul><li>Lead incident response and root cause analysis (RCA) for critical production issues</li><li>Define upgrade strategies, change management procedures, and disaster recovery plans</li><li>Write and maintain runbooks, operational playbooks, and knowledge base content</li><li>Integrate organizational processes, compliance requirements, and security policies into operational frameworks</li><li>Deep Linux expertise:</li><li>Kernel tuning (CPU governor, NUMA, IRQ affinity, hugepages)</li><li>Storage I/O scheduling, NVMe optimization</li><li>Network stack tuning for RDMA / InfiniBand</li><li>System performance profiling and bottleneck analysis</li></ul> 
Candidate Profile &mdash; Who You Are<ul><li>you are comfortable running production systems.</li><li>You have stronger SysOps and HPC depth than DevOps breadth, and you embrace that identity</li><li>You can shift fluidly between running a live incident, presenting an architecture to a CTO, and reviewing a POC demo environment</li><li>You communicate technical complexity clearly &mdash; to engineers and to C-level stakeholders</li><li>You understand why specific tooling choices matter (not just how to configure them) and can articulate trade-offs in presales conversations</li><li>You are comfortable owning outcomes across both commercial (presales) and delivery (operations) dimensions</li><li>You thrive in ambiguity and can scope both short POCs and long-horizon platform programs</li></ul> 
Requirements 
Required<ul><li>10+ years in platform/infrastructure engineering, with at least 2 years in architect-level role</li><li>Proven hands-on experience operating Kubernetes at scale in production (multi-cluster, multi-tenant)</li><li>Significant Linux systems administration experience &mdash; kernel, networking, storage at a low level</li><li>HPC and/or GPU infrastructure experience &mdash; physical GPU servers, NCCL, InfiniBand, or high-speed fabrics</li><li>Demonstrable presales or client-facing experience
</li><li>IaC experience: Terraform and/or Ansible in production environments</li><li>Strong understanding of GitOps and CI/CD pipelines in enterprise settings</li></ul> 
Strongly Preferred<ul><li>Experience with NVIDIA GPU Operator, MIG partitioning, Run:AI, or equivalent GPU scheduling tooling</li><li>Knowledge of distributed AI training infrastructure (PyTorch DDP, Horovod, DeepSpeed) from an infrastructure perspective</li><li>Familiarity with NVIDIA Triton Inference Server or TensorRT deployment pipelines</li><li>Experience with Weka, Ceph, or GPUDirect Storage in HPC/AI environments</li><li>Hands-on experience with Vault, External Secrets, and zero-trust network architectures</li><li>Exposure to bare-metal provisioning and HPC cluster management (Slurm, PBS, or equivalent)</li></ul> 
Certifications (Advantageous)<ul><li>CKA / CKS (Certified Kubernetes Administrator / Security Specialist)</li><li>RHCE / RHCA (Red Hat Certified Engineer / Architect)</li><li>AWS Solutions Architect / Azure Solutions Architect Expert</li><li>HashiCorp Terraform Associate or Vault Associate</li><li>NVIDIA DLI certifications (GPU computing, AI infrastructure)</li></ul> 
Benefits 
<ul><li>
Why Integrant?
</li><li>Competitive compensation package
</li><li>PTO, full medical and dental coverage, etc.
</li><li>Opportunity to travel and work onsite with U.S. customers
</li><li>In-house Technical and English training programs
</li><li>Dedicated learning time (check out our 4Plus1 Program) [link]
</li><li>Interest free loans
</li><li>Flexible work schedules
</li><li>Perks: events, sponsored lunch, game area, rooftop hangout + more!</li></ul></div>

Devops & SysOps Architect

Cognizant

About the Role
 As a Java AWS Architect , you will make an impact by designing and delivering scalable, secure, and high-performing enterprise applications using Java and AWS technologies. You will be a valued member of the engineering team and work collaboratively with Product, UX, Design, DevOps, and development teams to build enterprise authentication solutions and modern cloud-native applications from the ground up. In This Role, You Will:
 Architect, design, and develop enterprise applications using Java, Spring Boot, and Spring Security.
 Design and implement scalable, secure, and cloud-native solutions on AWS.
 Lead technical design discussions and guide engineering teams on architecture and development best practices.
 Design, develop, and maintain RESTful APIs, including API documentation using Swagger/OpenAPI.
 Partner with Product, UX, and Design teams to build enterprise authentication and authorization applications from scratch.
 Develop high-quality, testable code with strong unit testing practices to support CI/CD and DevOps initiatives.
 Build and maintain GitLab CI/CD pipelines leveraging tools such as SonarQube and Veracode.
 Conduct code reviews, enforce coding standards, and promote GitFlow development processes.
 Optimize applications for performance, scalability, reliability, and maintainability.
 Mentor developers and provide technical leadership throughout the software development lifecycle. Work Model
 We believe hybrid work is the way forward as we strive to provide flexibility wherever possible. Based on this role’s business requirements, this is a hybrid position requiring 3 days a week in a client or Cognizant office in Atlanta, Georgia or Raleigh, North Carolina .
 Regardless of your working arrangement, we are here to support a healthy work-life balance through our various wellbeing programs.
 The working arrangements for this role are accurate as of the date of posting. This may change based on the project you're engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations. What You Need to Have to Be Considered
 12+ years of experience designing and developing enterprise applications.
 Strong hands-on expertise in Java, Spring Boot, and Spring Security.
 Extensive experience architecting and implementing cloud-based solutions on AWS.
 Proven ability to make architecture decisions and provide technical leadership across teams.
 Strong SQL and database design expertise.
 Deep experience designing, developing, and integrating RESTful APIs.
 Experience implementing and managing Swagger/OpenAPI documentation.
 Hands-on experience with GitLab CI/CD pipelines.
 Experience using SonarQube, Veracode, and related code quality and security tools.
 Strong understanding of software engineering best practices, code reviews, testing, and DevOps methodologies.
 Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field, or equivalent professional experience. These Will Help You Stand Out
 Experience building enterprise authentication, identity, and access management solutions.
 AWS certifications such as AWS Certified Solutions Architect or AWS Certified Developer.
 Experience with microservices and distributed system architectures.
 Experience mentoring engineers and leading technical teams.
 Strong stakeholder management and communication skills.
 Experience working in Agile/Scrum environments. Salary and Other Compensation
 The annual salary for this position depends on experience and other qualifications of the successful candidate.
 This position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans. Benefits
 Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:
 Medical/Dental/Vision/Life Insurance
 Paid Holidays plus Paid Time Off
 401(k) Plan and Contributions
 Long-term/Short-term Disability
 Paid Parental Leave
 Employee Stock Purchase Plan Disclaimer
 The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.

Java AWS Architect

Logic, Inc.

<div><div>Advanced App/Cloud Support &amp; Engineering Team Lead/Consultant | Mid-Level | Full time
</div><div>Job No. 14612412 | New York City, NY</div></div>
 <div><div>Accenture Flex offers you the flexibility of local fixed-duration project-based work powered by Accenture, a leading global professional services company. Accenture is consistently recognized on FORTUNE's 100 Best Companies to Work For and Diversity Inc's Top 50 Companies For Diversity lists.
As an Accenture Flex employee, you will apply your skills and experience to help drive business transformation for leading organizations and communities. In addition to delivering innovative solutions for Accenture's clients, you will work with a highly skilled, diverse network of people across Accenture businesses who are using the latest emerging technologies to address today's biggest business challenges.
You will receive competitive rewards and access to benefits programs and world-class learning resources. Accenture Flex employees work in their local metro area onsite at the project, significantly reducing and/or eliminating the demands to travel.
Key Responsibilities:<ul><li>
Leads the design and implementation of enterprise DevOps and cloud engineering strategies to enable secure, scalable, and automated software delivery.</li><li>
Partners with architecture, development, security, and operations teams to define DevOps standards, build CI/CD frameworks, and drive infrastructure automation.</li><li>
Provides technical leadership, mentors DevOps engineers, coaches delivery teams on best practices, and coordinates cross-functional efforts to improve reliability, security, and operational excellence.</li><li>
Drives continuous improvement, governance, and adoption of DevSecOps, Infrastructure as Code (IaC), cloud-native architectures, and platform engineering practices.</li></ul></div></div>
 <div>Basic Qualifications:
<ul><li>
DevOps Architecture - 2+ years</li><li>
DevOps Coaching - 1+ year</li><li>
Configuration Release Management - 3+ years</li><li>
High School Diploma or GED</li></ul>

Preferred Qualifications:
<ul><li>
Associate or bachelor's Degree</li></ul>

Compensation at Accenture varies depending on a wide array of factors, which may include but are not limited to the specific office location, role, skill set, and level of experience. As required by local law, Accenture provides a reasonable range of compensation for roles that may be hired as set forth below. We anticipate this job posting will be posted until 08/07/2026.

<div>Accenture Flex offers a market competitive suite of benefits including medical, dental, vision, and long-term disability coverage, a 401(k) plan, and paid time off. See more information on our benefits here:
Accenture Flex Jobs
</div>
Role Location

California &ndash; $58.00 - $68.00/hour

Cleveland &ndash; $58.00 - $68.00/hour

Colorado &ndash; $58.00 - $68.00/hour

District of Columbia &ndash; $58.00 - $68.00/hour

Illinois - $58.00 - $68.00/hour

Maine - $58.00 - $68.00/hour

Maryland &ndash; $58.00 - $68.00/hour

Massachusetts &ndash; $58.00 - $68.00/hour

Minnesota - $58.00 - $68.00/hour

New Jersey/New York &ndash; $58.00 - $68.00/hour

Virginia - $58.00 - $68.00/hour

Washington &ndash; $58.00 - $68.00/hour</div>
 <div>New York City, NY</div>
 <div>Requesting an Accommodation

Accenture is committed to providing equal employment opportunities for persons with disabilities or religious observances, including reasonable accommodation when needed. If you are hired by Accenture and require accommodation to perform the essential functions of your role, you will be asked to participate in our reasonable accommodation process. Accommodations made to facilitate the recruiting process are not a guarantee of future or continued accommodations once hired.

If you would like to be considered for employment opportunities with Accenture and have accommodation needs such as for a disability or religious observance, please call us toll free at 1 (877) 889-9009 or send us an email or speak with your recruiter. 


Equal Employment Opportunity Statement

We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities. 


Accenture is an EEO and Affirmative Action Employer of Veterans/Individuals with Disabilities.

Accenture is committed to providing veteran employment opportunities to our service men and women. 


Other Employment Statements

Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization in the United States.

Candidates who are currently employed by a client of Accenture or an affiliated Accenture business may not be eligible for consideration.

Job candidates will not be obligated to disclose sealed or expunged records of conviction or arrest as part of the hiring process. Further, at Accenture a criminal conviction history is not an absolute bar to employment. 
 
The Company will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. Additionally, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the Company's legal duty to furnish information.

California requires additional notifications for applicants and employees. If you are a California resident, live in or plan to work from Los Angeles County upon being hired for this position, please for additional important information.

Please read Accenture&rsquo;s Recruiting and Hiring Statement for more information on how we process your data during the Recruiting and Hiring process.</div>
 <div>We work with one shared purpose: to deliver on the promise of technology and human ingenuity. Every day, more than 775,000 of us help our stakeholders continuously reinvent. Together, we drive positive change and deliver value to our clients, partners, shareholders, communities, and each other.

We believe that delivering value requires innovation, and innovation thrives in an inclusive and diverse environment. We actively foster a workplace free from bias, where everyone feels a sense of belonging and is respected and empowered to do their best work.

At Accenture, we see well-being holistically, supporting our people&rsquo;s physical, mental, and financial health. We also provide opportunities to keep skills relevant through certifications, learning, and diverse work experiences. We&rsquo;re proud to be consistently recognized as one of the World&rsquo;s Best Workplaces&trade;.

Join Accenture to work at the heart of change. Visit us at www.accenture.com.</div>

Senior DevOps Engineer - 6426315

Maximus

<div>Maximus TCS (Technology and Consulting Services) Internal Job Profile Code: TCS195, T3, Band 6
Job-Specific Essential Duties and Responsibilities:
<ul><li>Architect and operate enterprise Kubernetes clusters.
</li><li>Implement security hardening and compliance within container platforms
</li><li>Define container platform standards and governance.
</li><li>Provide architecture guidance for containerized applications to Lead Cloud Architect and government stakeholders.
</li><li>Ensure scalability, performance, and security of container workloads.
</li><li>Integrate Kubernetes into CI/CD pipelines and cloud platforms.
</li><li>Support multi-cloud container orchestration strategies.
</li><li>Support monitoring and logging for container environments.
</li><li>Collaborate with cloud architects and engineering teams
</li></ul>Job-Specific Minimum Requirements:
<ul><li>Active Secret security clearance.
</li><li>Ability to commute on-site as needed to San Antonio, Texas.
</li><li>5+ years Kubernetes platform experience.
</li><li>Advanced certification (CKA, CKS).
</li><li>Active IAT/IAM Level II certification
</li></ul>Preferred Skills and Qualifications:
<ul><li>Experience with DoD cloud environments (e.g., Platform One, Cloud Once, AWS Gov Cloud, etc.) and Kubernetes-based PaaS.
</li><li>Expertise with service mesh (Istio/Linkerd) and ingress architectures.
</li><li>Experience in multi-cluster / multi-region deployments to include scaling best practices and related strategies.
</li><li>Knowledge of container security (runtime protection, image scanning).
</li><li>Familiarity with GitOps (ArgoCD, Flux) and platform automation.
</li></ul>#techjobs #clearance #veteransPage
Minimum Requirements
 
 
TCS195, T3, Band 6
EEO Statement
 
 
Maximus is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, age, national origin, disability, veteran status, genetic information and other legally protected characteristics.
Pay Transparency
 
 
Maximus compensation is based on various factors including but not limited to job location, a candidate's education, training, experience, expected quality and quantity of work, required travel (if any), external market and internal value analysis including seniority and merit systems, as well as internal pay alignment. Annual salary is just one component of Maximus's total compensation package. Other rewards may include short- and long-term incentives as well as program-specific awards. Additionally, Maximus provides a variety of benefits to employees, including health insurance coverage, life and disability insurance, a retirement savings plan, paid holidays and paid time off. Compensation ranges may differ based on contract value but will be commensurate with job duties and relevant work experience. An applicant's salary history will not be used in determining compensation. Maximus will comply with regulatory minimum wage rates and exempt salary thresholds in all instances.
Accommodations
 
Maximus provides reasonable accommodations to individuals requiring assistance during any phase of the employment process due to a disability, medical condition, or physical or mental impairment. If you require assistance at any stage of the employment process-including accessing job postings, completing assessments, or participating in interviews,-please contact People Operations at applicantaccom@maximus.com .
Minimum Salary 
$140,000.00
Maximum Salary 
$160,000.00</div>

Kubernetes Architect

Photon

<div><div>Job Summary:
The Agentic AI Architect / Technical Lead will serve as the primary technical authority for designing and delivering large-scale Agentic AI solutions. This role acts as a critical bridge between product strategy, customer requirements, and engineering execution, requiring a strong blend of AI expertise, system architecture, and leadership skills.
The Architect will be responsible for leading architecture definition, driving complex proof-of-concept initiatives, enabling multi-agent system design, and managing cross-functional engineering teams. The role demands deep experience in LLM ecosystems, cloud-native platforms, and scalable system design to deliver robust, production-grade AI platforms with measurable business outcomes.
Key Responsibilities:
Solution Architecture: Lead the design and development of scalable, secure, and high-performance architectures for Agentic AI platforms using Python and modern frameworks
Technical Standards &amp; Deliverables: Define architecture patterns, engineering standards, and best practices for development, deployment, and system scalability
Collaboration: Work closely with product managers, engineering teams, DevOps, and QA to align technical solutions with business requirements and ensure seamless system integration
Stakeholder Interaction: Lead and execute technical POCs for Agentic AI solutions, working with customer stakeholders to define success criteria, build tailored agent configurations, and demonstrate business impact
Agent Orchestration: Architect and implement multi-agent workflows using frameworks such as LangGraph, AutoGen, or CrewAI, ensuring alignment with real-world use cases
Platform Development: Design and build resilient, scalable, multi-tenant AI platforms that support continuous innovation and production deployment
Evaluation &amp; Benchmarking: Own the design and implementation of LLM and agent evaluation frameworks, including metrics for accuracy, hallucination, safety, and performance
Performance Optimization: Optimize system architecture and infrastructure for scalability, latency, and cost-efficiency across AI workloads
Best Practices: Establish and enforce standards across MLOps, AIOps, CI/CD, model versioning, experimentation tracking, and system observability
Leadership &amp; Mentorship: Provide technical leadership, guide architectural decisions, and mentor engineering teams to ensure high-quality delivery
Innovation &amp; Research: Stay updated with advancements in AI, LLMs, and agentic frameworks, continuously improving system capabilities
Documentation: Create and maintain comprehensive architectural and technical documentation
Required Skills &amp; Qualifications:
<ul><li>12+ years of experience in software engineering with strong expertise in Python and backend system development
</li><li>Extensive experience in designing scalable, secure, multi-tenant AI/ML platforms
</li><li>Deep expertise in LLMs (OpenAI, Gemini, Anthropic, Llama) and agentic AI systems
</li><li>Hands-on experience with agent frameworks such as AutoGen, CrewAI, LangGraph, and LangChain ecosystem (LangChain, LangSmith, LangFlow)
</li><li>Strong experience building RAG-based systems and working with vector databases
</li><li>Proficiency in Python ecosystem including PyTorch, Scikit-learn, LlamaIndex, and evaluation tools like DeepEval
</li><li>Deep understanding of LLM concepts (prompt engineering, fine-tuning, function/tool calling, RAG)
</li><li>Strong experience in microservices architecture, REST APIs, and event-driven systems
</li><li>Expertise in relational (PostgreSQL, MySQL) and NoSQL databases (MongoDB, Redis)
</li><li>Experience with cloud platforms (AWS, Azure, GCP) and cloud-native architectures
</li><li>Familiarity with Docker, Kubernetes , and modern DevOps practices
</li><li>Experience with CI/CD pipelines (Jenkins, GitLab CI, GitHub Actions)
</li><li>Strong exposure to observability tools for logging, monitoring, and tracing AI systems
</li><li>Strong understanding of system design, scalability, and engineering best practices
</li><li>Proven ability to lead architectural discussions, mentor teams, and engage with stakeholders and clients
</li></ul>Compensation, Benefits and Duration
Minimum Compensation: USD 46,000
 
Maximum Compensation: USD 162,000
 
Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role.
 
Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full time employees.
 
This position is not available for independent contractors
 
No applications will be considered if received more than 120 days after the date of this post.</div></div>

Technical Lead - Dallas, TX

Valeo

<div>
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Deploy and maintain secure cloud infrastructure primarily on GCP (Google Cloud Platform) and AWS, ensuring seamless integration between services.
 </li>
 <li>
 Manage and optimize GKE (Google Kubernetes Engine) clusters for high-availability AI applications and microservices.
 </li>
 <li>
 Infrastructure as Code: Build and enforce Terraform strategies to provision and manage infrastructure, ensuring environments are reproducible and version-controlled.
 </li>
 <li>
 CI/CD &amp; Software Verification: Design and implement advanced CI/CD workflows using GitHub Actions, moving beyond simple deployments to create intelligent automation.
 </li>
 <li>
 Build robust verification pipelines that include automated testing, linting, security scanning, and quality gates before production release.
 </li>
 <li>
 Streamline the release process for backend and frontend applications, ensuring "one-click" reliability.
 </li>
 <li>
 Oversee the deployment, maintenance, and backup strategies for databases.
 </li>
 <li>
 Implement comprehensive monitoring and logging solutions (Prometheus, Grafana, Cloud Ops, Cloud Monitoring) to ensure system health, performance, and rapid incident response.
 </li>
 <li>
 Implement security best practices (IAM, VPC configuration, encryption) to protect sensitive AI data and intellectual property.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 
 
 Education &amp; Experience
 
 
 
 
 <ul>
 <li>
 B.Sc. or M.Sc. in Computer Science, Computer Engineering, or a related technical field.
 </li>
 <li>
 5+ years of relevant experience in DevOps, Cloud Engineering, or Site Reliability Engineering (SRE).
 </li>
 <li>
 Proven experience acting as a Senior or Lead engineer, guiding architectural decisions.
 
 
 </li>
 </ul>
 
 
 Technical Requirements
 
 
 
 
 <ul>
 <li>
 Advanced hands-on experience with GCP (specifically GKE, VPC, IAM) and a working knowledge of AWS.
 </li>
 <li>
 Proven ability to design and implement robust, scalable, and secure cloud architectures.
 </li>
 <li>
 Mastery of Docker and Kubernetes administration.
 </li>
 <li>
 Strong proficiency in Terraform.
 </li>
 <li>
 Expert knowledge of GitHub Actions for building, test, build, and deploy pipelines.
 </li>
 <li>
 Experience managing PostgreSQL and ClickHouse databases.
 </li>
 <li>
 Deep understanding of Linux System Administration.
 </li>
 <li>
 Experience with AI/ML lifecycle tools (e.g., Kubeflow, MLflow, Vertex AI).
 </li>
 <li>
 Strong proficiency in Python and Bash scripting.
 </li>
 <li>
 Familiarity with DevSecOps tools and practices.
 </li>
 <li>
 Bonus: Official GCP Certifications (e.g., Professional Cloud Architect, Professional Cloud DevOps Engineer) and Kubernetes Certifications (e.g., CKA, CKAD, CKS) are highly preferred.
 </li>
 <li>
 Bonus: Knowledge of Javascript/Node.js is a strong plus.
 
 
 </li>
 </ul>
 
 
 Soft Skills &amp; Mindset
 
 
 
 
 <ul>
 <li>
 Ability to design long-term solutions rather than quick fixes.
 </li>
 <li>
 Excellent ability to explain complex cloud concepts to Data Scientists and business stakeholders.
 </li>
 <li>
 Comfortable working in a fast-paced environment with evolving requirements.
 </li>
 <li>
 Fluent English is a must.
 </li>
 </ul>
</div>

Senior DevOps Engineer, AI4ALL

Park Place Technologies

<div>AI Software Architect

The AI Software Architect is responsible for participating in all aspects of the software development life cycle from requirement gathering through user acceptance testing and implementation. In addition, this position will participate in the establishment and enforcement of programming patterns and standards, as well as provide mentorship to junior developers. 


Responsibilities: 

<ul>
<li>Collaborate with BAs and end users to interpret requirements into a technical design through onsite requirements gathering sessions, workshops, and solution design reviews.</li>
<li>Develop software according to end user requirements and quality standards.</li>
<li>Identify, document and implement programming patterns and set standards.</li>
<li>Perform code reviews to enforce patterns and standards in our code base while facilitating in-person knowledge sharing and architectural consistency across teams.</li>
<li>Lead POCs, design sessions, and pair programming efforts.</li>
<li>Mentor junior team members.</li>
<li>Participate in project planning and/or provide accurate estimates on projects/tasks through cross-functional planning meetings and stakeholder alignment discussions.</li>
<li>Participate in Story Card Grooming and Sprint Planning as requested.</li>
<li>Be available as needed to support production deployments.</li>
<li>Possess strong organizational and process analysis skills.</li>
<li>Effectively communicate both orally and in writing and manage multiple assignments and priorities.</li>
<li>Actively teach best practices and new technologies.</li>
<li>Hold teaching sessions at least once a year.</li>
<li>Facilitate daily standups and lead sprint demos as needed.</li>
<li>Assist managing the Azure DevOps task board as needed.</li>
<li>Assist with onboarding and training new resources.</li>
<li>Participate in interviews upon request.</li>
<li>Support, troubleshoot and resolve production issues, including facilitating in-person incident response discussions and cross-functional problem resolution when required.</li>
<li>Demonstrate willingness to work on your craft and take initiative in learning new skills.</li>
<li>Other duties as assigned.</li></ul> 


Basic Qualifications: 

<ul>
<li>Subject Matter Expert with Visual Studio, GIT and Azure DevOps</li>
<li>10+ years of application development experience across the following technologies:</li>
</ul><ul><li><ul><li>.Net Framework/Core</li>
<li>Angular</li>
<li>C#</li>
<li>JSON</li>
<li>SCSS/SASS</li>
<li>SQL</li>
<li>Test Driven Development/Unit Testing</li>
<li>Typescript, ES6</li>
<li>Web API/Rest</li>
<li>Agile Methodology</li>
<li>Asynchronous Programming</li>
<li>Azure Data Bricks</li>
<li>Azure Data Factory</li>
<li>Azure Functions</li>
<li>Azure Logic Apps</li>
<li>Azure PAAS</li>
<li>Browser Compatibility Testing</li>
<li>Cosmos DB</li>
<li>CQRS Pattern</li>
<li>Dependency Injection</li>
<li>Entity Framework &amp; LINQ</li>
<li>MicroServices</li>
<li>OData</li>
<li>Python</li></ul></li></ul> 

In addition to core software architecture duties, this position will lead the design, integration, and governance of AI/ML-driven solutions across the application portfolio, ensuring responsible and scalable adoption of AI capabilities. 


Additional Responsibilities 

<ul>
<li>Architect and design solutions incorporating AI/ML components, including LLM-based features, intelligent automation, and predictive models.</li>
<li>Evaluate and select appropriate AI frameworks, models, and platforms (e.g., Azure AI/OpenAI services, LangChain, vector databases) based on business requirements and technical constraints.</li>
<li>Design and implement Retrieval-Augmented Generation (RAG) pipelines, prompt engineering strategies, and model orchestration patterns.</li>
<li>Establish patterns and standards for responsible AI use, including data privacy, model governance, bias mitigation, and explainability.</li>
<li>Collaborate with data engineering and data science teams to integrate AI/ML models into production applications and CI/CD pipelines.</li>
<li>Design scalable architectures for embedding generation, semantic search, and vector storage/retrieval.</li>
<li>Evaluate build-vs-buy tradeoffs for AI tooling and vendor platforms.</li>
<li>Monitor AI solution performance, cost, and accuracy in production, and drive continuous improvement.</li>
<li>Stay current on emerging AI/ML technologies, LLM capabilities, and industry best practices, and evangelize relevant advances to engineering teams.</li>
<li>Mentor developers on AI-assisted development tools and practices (e.g., AI coding assistants, automated testing/generation tools).</li>
<li>Partner with security and compliance teams to ensure AI solutions meet regulatory and data governance requirements.</li></ul> 


Additional Basic Qualifications 

<ul>
<li>Demonstrated experience architecting or building solutions using Large Language Models (LLMs) and generative AI.</li>
<li>Experience with prompt engineering, RAG architectures, and vector databases (e.g., Cosmos DB vector search, Pinecone, Azure AI Search).</li>
<li>Familiarity with AI/ML orchestration frameworks (e.g., LangChain, Semantic Kernel) and MLOps practices.</li>
<li>Working knowledge of Python-based AI/ML libraries and APIs (e.g., OpenAI SDK, Azure OpenAI, Hugging Face).</li>
<li>Understanding of responsible AI principles: data privacy, model bias, explainability, and governance.</li>
<li>Experience integrating AI capabilities into cloud-native (Azure) application architectures.</li></ul> 


Education: 

<ul>
<li>Bachelor&rsquo;s degree or higher in Computer Science or related degree is preferred.</li></ul> 


Travel: 

<ul>
<li>&lt;5%</li></ul> 


If you are a qualified individual with a disability or a disabled veteran, you may request a reasonable accommodation if you are unable or limited in your ability to access job openings or apply for a job on this site as a result of your disability. You can request reasonable accommodations by calling 1-877-778-8707. 


Park Place Technologies is an Equal Opportunity Employer M/F/D/V. 


Park Place Technologies has an in-house recruiting team that focuses exclusively on the hiring needs of our company. We are not currently accepting additional third-party agreements or unsolicited resumes. If you would like to be considered as a preferred partner with Park Place Technologies, please submit your detailed information to careers@parkplacetech.com. Any CVs submitted directly to hiring managers will be considered unsolicited and become the property of Park Place Technologies.
Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities 
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights (https://www.eeoc.gov/poster) notice from the Department of Labor.</div>

AI Software Architect

Search 479+ Devops architect jobs near you this August. New roles added regularly across leading industries. Apply today.