cloud ai engineer

DATA PULSE TECH AI LLC

<p><b>Generative AI &amp; Machine Learning | Google Cloud Platform | Federal Program</b></p><p><b>Location:</b> Remote (United States) &mdash; occasional travel may be required<br/><b>Employment Type:</b> Full-Time (Contract)<br/><b>Rate:</b> $100 &ndash; $150 per hour (commensurate with experience)<br/><b>Level:</b> Mid-Senior / SME (3&ndash;6+ years)<br/><b>Citizenship:</b> <b>U.S. Citizenship required &mdash; no exceptions, no visa sponsorship, no C2C through third-party visa holders</b><br/><b>Clearance:</b> Must be able to obtain and maintain Minimum Background Investigation (MBI)</p><p><b>About the Role</b></p><p><b>Lanthos Tech</b> is seeking a <b>GCP AI Engineer (SME)</b> to design, build, and scale a production-grade AI research system on Google Cloud Platform.</p><p>This role sits at the intersection of applied AI, software engineering, and federal compliance. You will build Retrieval-Augmented Generation (RAG) pipelines, deploy models through Vertex AI, and integrate Gemini APIs &mdash; all within a FedRAMP-authorized, ATO-governed cloud environment. It suits an engineer who is equally comfortable writing production Python, architecting cloud infrastructure, and reasoning about model behavior, latency, cost, and auditability.</p><p><b>What You'll Do</b></p><ul><li>Design, build, and deploy machine learning and generative AI pipelines on <b>Vertex AI</b>, including model training, fine-tuning, evaluation, and serving.</li><li>Build <b>RAG architectures</b> using vector search (e.g., Vertex AI Vector Search) to ground LLM outputs .</li><li>Integrate <b>Gemini APIs</b> and other foundation models into mission applications and internal analyst tooling.</li><li>Develop agentic workflows and multi-step orchestration using frameworks such as <b>LangChain, LangGraph, or CrewAI</b>.</li><li>Build and deploy agents using <b>Google's Agent Development Kit (ADK)</b> and integrate them with <b>Gemini Enterprise</b> for enterprise-grade deployment, access control, and governance.</li><li>Operate agents within managed runtime environments (e.g., <b>Vertex AI Agent Engine</b>), handling session state, tool-calling, and scaling of long-running agent workloads.</li><li>Architect and maintain scalable, secure cloud infrastructure across GCP services (<b>BigQuery, Cloud Run, Pub/Sub, Cloud Functions, GKE</b>), using <b>FedRAMP-authorized services and government-approved regions</b>.</li><li>Implement <b>MLOps</b> practices: CI/CD for models, automated retraining, monitoring, drift detection, evaluation harnesses, and rollback strategies.</li><li>Design systems that meet federal security and privacy obligations.</li><li>Support the <b>Authority to Operate (ATO)</b> process by producing architecture artifacts, data-flow diagrams, and control evidence in partnership with the security and compliance lead.</li><li>Write clean, well-tested, production-quality <b>Python</b>.</li><li>Collaborate with data scientists, product managers, platform engineers, and government stakeholders to translate mission requirements into technical solutions.</li><li>Monitor and optimize model performance, latency, and inference cost in production.</li><li>Document architecture decisions, pipelines, model cards, and operational runbooks for maintainability and government handover.</li></ul><p><b>Required Technical Skills</b></p><p><b>Programming</b></p><ul><li>Strong proficiency in <b>Python</b>; working knowledge of JavaScript or TypeScript is a plus.</li></ul><p><b>GCP &amp; AI Tools</b></p><ul><li>Hands-on experience with <b>Vertex AI</b> (training, pipelines, endpoints, model registry).</li><li>Experience with <b>Gemini APIs</b> and other GCP AI/ML services.</li><li>Proficiency with <b>BigQuery</b> for data warehousing and analytics workloads.</li></ul><p><b>GenAI &amp; Frameworks</b></p><ul><li>Solid understanding of <b>RAG architectures</b> and vector database implementations.</li><li>Experience with agentic orchestration frameworks: <b>LangChain, LangGraph, CrewAI</b>, or equivalent.</li><li>Hands-on experience with <b>Google's Agent Development Kit (ADK)</b> for building, testing, and deploying agents.</li><li>Familiarity with <b>Gemini Enterprise</b> for enterprise agent deployment, access control, and governance.</li><li>Experience operating agents in a <b>managed agent runtime</b> (e.g., Vertex AI Agent Engine), including session/state management and tool orchestration at scale.</li><li>Familiarity with prompt engineering, embeddings, and <b>LLM evaluation techniques</b> (groundedness, hallucination detection, retrieval quality).</li></ul><p><b>ML Operations</b></p><ul><li>Demonstrated ability to scale, monitor, and automate ML pipelines in production.</li><li>Experience with containerization (<b>Docker</b>) and orchestration (<b>Kubernetes / GKE</b>).</li><li>Familiarity with CI/CD tooling (<b>Cloud Build, GitHub Actions</b>, or similar).</li></ul><p><b>Federal Eligibility Requirements</b></p><p>These are contractual requirements and are not negotiable:</p><ul><li><b>Must be a U.S. Citizen.</b> Documentation of citizenship will be required. Permanent residents, visa holders, and dual-status candidates requiring sponsorship are not eligible for this engagement.</li><li><b>Must reside in and perform all work from within the United States.</b> Offshore or overseas work is prohibited.</li><li>Must be able to <b>pass an background investigation (Public Trust / MBI)</b>, including fingerprinting, and a <b>favorable federal tax compliance check</b> (filed and current on all tax obligations).</li><li>Must complete required federal security, privacy, and Safeguards (Pub 1075) training prior to system access.</li></ul><p><b>Qualifications &amp; Education</b></p><ul><li>Bachelor's degree in Computer Science, Engineering, or equivalent practical experience. Master's or PhD preferred for senior/SME-level scope.</li><li><b>3&ndash;6+ years</b> of software development or production AI/ML engineering experience.</li><li>Prior experience deploying AI/ML systems in a <b>production, end-user-facing environment</b> strongly preferred.</li><li>Prior <b>federal, public sector, or other regulated-industry</b> delivery experience is a significant advantage.</li></ul><p><b>Preferred Certifications</b></p><ul><li><b>Google Cloud Professional Machine Learning Engineer</b> (recommended).</li><li>Google Cloud Professional Cloud Architect or Professional Data Engineer (a plus).</li></ul><p><b>Nice to Have</b></p><ul><li>Experience with multi-agent systems or autonomous agent design.</li><li>Prior work in a <b>FedRAMP</b> or <b>ATO-governed</b> cloud environment.</li><li>Familiarity with <b>Section 508 / accessibility</b> requirements for government-facing applications.</li><li>Experience handling PII, FTI, or other sensitive data under formal safeguards.</li><li>Contributions to open-source ML/AI tooling.</li><li>Familiarity with cost optimization strategies for large-scale inference workloads.</li></ul><p><b>Compensation &amp; Engagement Details</b></p><ul><li><b>$100 &ndash; $150 per hour</b>, based on experience, certifications, and depth of GCP AI delivery history.</li><li>Full-time contract engagement supporting a federal program.</li><li>100% remote within the United States.</li><li>Professional development and certification support available.</li></ul><p><b>Interview Process</b></p><ul><li><b>Recruiter screen</b> &mdash; eligibility, experience, and availability.</li><li><b>Round 1: Technical interview</b> (60 minutes) &mdash; GCP AI/ML depth, RAG and agent architecture, hands-on scenarios.</li><li><b>Round 2: Leadership interview</b> &mdash; delivery experience, collaboration, and federal program fit.</li><li><b>Additional round</b> may be scheduled on a need basis.</li><li><b>Onboarding</b> &mdash; citizenship verification, background investigation, and tax compliance check.</li></ul><p><i>Lanthos Tech is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. The U.S. citizenship and background investigation requirements stated above are imposed by the terms of the federal contract this position supports.</i></p><p>Pay: $90.00 - $150.00 per hour</p><p>Application Question(s):</p><ul><li>Are you a U.S Citizen ? </li></ul><p>Work Location: Remote</p>

GCP AI Engineer — Subject Matter Expert (SME)

Intégral

<div>Overview:
<div><b>
Agentic Engineer</b></div><div><b>
Location: Tysons Corner, VA (Hybrid)</b></div><div></div><div><br>
At Integral Federal, we invest in our people&mdash;equipping them with the tools, expertise, and culture of innovation needed to deliver measurable results. Committed to exceeding expectations and delivering mission impact, our team thrives on solving complex challenges, optimizing performance, and ensuring long-term success for our clients.</div><div></div><div><b><br>
The Role:</b> We are looking for a curious builder to join our team and develop AI Agents. You will design, build, and deploy autonomous agents and LLM-powered applications across AWS, Google Cloud, and Microsoft Azure.</div><div></div><div><br>
We do not require a Master&rsquo;s degree, a Bachelor&rsquo;s degree, or any degree at all. We care about your understanding of modern AI architectures and your drive to repetitively solve problems. If you are the type of developer who loves tinkering with multi-agent workflows, experimenting with the Model Context Protocol (MCP), and testing the limits of new foundation models, you belong here.</div><div></div><div><b><br>
Work Authorization</b>: Candidates must be authorized to work in the U.S. without the need for an employer-sponsored visa now or in the future.</div>
Responsibilities:
<ul><li>Design and build autonomous AI agents using the latest large language models (LLMs) and orchestration frameworks.</li><li>
Implement and leverage the Model Context Protocol (MCP) to seamlessly connect our AI models with external tools, APIs, and data sources.</li><li>
Move beyond prototypes by building rigorous evaluation (Evals) pipelines and implementing LLM observability to ensure agents run reliably without hallucinating or getting stuck in infinite tool-calling loops.</li><li>
Deploy AI solutions across multi-cloud environments, utilizing the best tools available on AWS, Google Cloud (GCP), and Microsoft Azure.</li><li>
Translate complex, ambiguous problems into functional, robust, production-ready code.</li><li>
Stay plugged into the bleeding edge of the AI landscape, bringing new tools, papers, and open-source projects to the team's attention.</li><li>
Work closely with other engineers to securely and efficiently integrate agentic workflows into our existing infrastructure.</li></ul>
Qualifications:
<div><b>
What You Must Bring (Required):</b></div><div></div><ul><li><b><br>
Proof of Capability:</b> Personal projects, GitHub repositories, or open-source contributions demonstrating your ability to build AI apps or agents. (Please include links in your application).</li><li><b>
LLM &amp; Agent Experience</b>: Hands-on experience working directly with LLM APIs (OpenAI, Anthropic, Gemini, etc.) and building agentic loops (tool calling, memory management, reasoning).</li><li><b>
Protocol Knowledge:</b> Familiarity with or a strong desire to master the Model Context Protocol (MCP) for tool integration.</li><li><b>
Cloud Fluency:</b> Experience deploying applications or running experiments on at least one major cloud provider (AWS, GCP, or Azure) and a willingness to learn the others.</li><li><b>
Builder&rsquo;s Mindset:</b> An insatiable curiosity, a high tolerance for ambiguity, and the grit to troubleshoot novel problems.</li></ul><div></div><div><b><br>
Bonus Points (Preferred):</b></div><br>
<div></div><ul><li>
Experience fine-tuning models or working with local, open-weight models.</li><li>
Experience testing models to create a baseline and identify drift</li><li>
Experience building custom tools, robust RAG pipelines, or complex data ingestion pipelines from scratch.</li></ul><div>
Salary range: $90,000 - $175,000</div><div>
The above salary range represents a general guideline. Integral Federal considers a number of factors when determining base salary offers, such as the scope and responsibilities of the position and the candidate's experience, education, skills, and current market conditions.</div><div>
Depending on the position, employees may be eligible for overtime, shift differential, and/or discretionary bonuses in addition to base pay.</div>
Company Overview:
<div>
Integral partners with federal defense, intelligence, and civilian leaders to tackle their most important challenges and deliver positive outcomes. Since our founding in 1998, we have helped clients leverage existing and emerging technologies to transform their enterprises, empower growth, drive innovation, and build sustainable success. The forward-leaning solutions we deliver are tailored to each mission with a focus on keeping our nation safe and secure.</div><div></div><div><br>
Integral is headquartered in McLean, VA and serves clients throughout the country.</div><div></div><div><br>
We offer a comprehensive total rewards package including paid parental leave and immediate vesting in our 401(k). Give us a try and become part of a curated group of professionals at Integral Federal!</div><div></div><div><br>
Our package also includes:</div><ul><li>Medical, Dental &amp; Vision Insurance</li><li>Flexible Spending Accounts</li><li>Short-Term and Long-Term Disability Insurance</li><li>Life Insurance</li><li>Paid Time Off &amp; Holidays</li><li>Earned Bonuses &amp; Awards</li><li>Professional Training Reimbursement</li><li>Employee Assistance Program</li></ul><div></div><div><br>
Equal Opportunity Employer/Protected Veteran/Disability</div></div>

Agentic Engineer

Nakupuna Companies

<div><div>Nakupuna Consulting seeks an AI Solutions Engineer for an Amazon Web Services (AWS) environment with strong technical expertise in constructing, developing and extending Retrieval-Augmented Generation (RAG) models. This individual will help the Defense POW/MIA Accounting Agency (DPAA) imagine and scope AI/ML use cases that will create the greatest value for the agency, define paths to navigate technical challenges, develop proof-of-concepts, and make plans for launching solutions at scale. The AI Engineer will design models using data from DPAA&rsquo;s Mission Application Suite &ndash; like military personnel case files and excavation site reports &ndash; to further identify missing personnel from previous conflicts. The position collaborates closely with customers and mission partners to develop innovative solutions that enhance DPAA&rsquo;s global efforts to locate, recover, and identify missing personnel through cutting-edge technologies and cross-functional teamwork. The AI Engineer will also collaborate with contractors and government IT professionals to accomplish system architecture and sustainment objectives.<br>
</div><br>
<p>The following reflects management&rsquo;s definition of essential functions for this job but does not restrict the tasks that may be assigned.
</p><div>Technical Responsibilities:</div><ul><li>
Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate generative AI solutions addressing real-world challenges.</li><li>
Engage directly with customers to understand their business problems and assist in the implementation of generative AI solutions.</li><li>
Brief customers and guide them on adoption strategies and production deployment pathways.</li><li>
Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations tailored to technical, business, and executive audiences.</li><li>
Provide customer and market feedback to product and engineering teams to influence product direction and roadmap.</li><li>
Implement data pipelines, vectorization methods, and API integrations using Python.</li><li>
Contribute to existing AI-enabled full-stack web projects built in Python and React.</li><li>
Utilize AWS AI/ML services such as Amazon SageMaker, Bedrock, and Comprehend for model development, fine-tuning, and orchestration.</li><li>
Manage structured and unstructured data using AWS storage and retrieval solutions like Amazon S3, OpenSearch, and Aurora.</li><li>
Apply vector database technologies such as FAISS, Pinecone, or OpenSearch vector search for document retrieval and similarity search.</li><li>
Integrate LLM APIs and apply prompt engineering techniques to connect retrieval systems with generative models.</li><li>
Demonstrate basic DevOps and security awareness on AWS, including IAM roles, networking (VPCs), and data encryption practices.</li><li>
Use containerization and orchestration tools such as Docker and AWS Lambda/ECS for scalable RAG (Retrieval-Augmented Generation) pipeline deployment.</li><li>
Utilize AWS Lambda to run responses triggered by alerts from integrated services.</li><li>
Support security and operations using AWS-native technologies, ensuring compliance with DoD security requirements.</li><li>
Evaluate and propose new AWS technologies and modernization paths to enhance operational efficiency and security with AI solutions.</li><li>
Develop and maintain Standard Operating Procedures (SOPs), technical documentation, and reports on system operations.</li><li>
Adhere to Agile program best practices such as participation and management of team scrums and sprint plannings.</li><li>
Document and track all work using the program approved ticketing system.</li></ul><div><b><br>
Skills/Qualifications:</b></div><ul><li>
Strong technical expertise in AWS GovCloud and Microsoft Windows Server environments.</li><li>
Excellent technical, organizational, decision-making, and analytical skills.</li><li>
Strong Python experience including object-oriented development.</li><li>
Experience with React or other frontend JavaScript web frameworks is a plus.</li><li>
Strong communication skills with the ability to engage both technical staff and executive stakeholders.</li><li>
Ability to enforce program best practices (ticketing, documentation, reporting).</li><li>
Familiarity with DoD IT environments, compliance requirements, and cybersecurity standards.</li><li>
Ability to adapt to a dynamic, fast-paced environment and support teams across geographically dispersed locations.</li></ul><div><b>
Education/Experience:</b></div><ul><li>
Bachelor&rsquo;s degree in a STEM field from an accredited institution, or equivalent years of related work or military experience.</li><li>
Minimum of 3 years of relevant professional experience, including systems administration and cloud operations.</li><li>
Experience supporting DoD IT environments preferred.</li><li>
Experience using Agile methodologies and ticketing systems such as JIRA is desirable.</li></ul><div><b>
Required Certification(s):</b></div><div>
Must have an active certification from the bullet list below</div><ul><li>
Active IAT II Certification which may include CompTIA Advanced Security Practitioner (CASP+), CompTIA Cybersecurity Analyst (CySA+), Certified Information Systems Security Professional (CISSP), or CompTIA Security+.</li><li>
AWS certification (e.g., AWS Certified AI Practitioner, AWS Certified Cloud Practitioner, AWS SysOps Administrator Associate, AWS Solutions Architect Associate)</li></ul><div><b>
Clearance Requirements:</b> Must currently have at least a Secret level security clearance in Hawaii and TS/SCI in Arlington, Virginia. Must be a U.S. citizen.</div><div></div><div><b><br>
Work Location:</b></div><ul><li>
Position may be based in either Arlington, VA or Honolulu, HI.</li><li>
Preferred: on-site three (3) days per week. Will consider fewer days on-site for the correct candidate.</li><li>
Occasional travel (1&ndash;2 weeks per year) within the Continental U.S. or to Hawaii may be required.</li><li>
This position may require working outside of normal business hours, including evenings and weekends, to meet operational or project demands.</li></ul><div><b>
Physical Requirements:</b> The ideal candidate must at a minimum be able to meet the following physical requirements of the job <i>with or without reasonable accommodation:</i></div><ul><li>
Ability to perform repetitive motions with the hands, wrists, and fingers.</li><li>
Ability to engage in and follow audible communications in emergency situations.</li><li>
Ability to sit for prolonged periods at a desk and working on a computer.</li></ul><div></div><div><br>
The Nakupuna Companies use a market-based compensation strategy to ensure that our employees are compensated within applicable market ranges commensurate with multiple factors, including but not limited to the individual&rsquo;s particular combination of education, knowledge, skills, competencies, and experience, as well as contract-specific affordability, organizational requirements, and position location. The projected compensation range for this position is $115,000.00 to $145,000.00 (annualized USD). The salary range displayed represents the typical salary range for this position and is just one component of Nakupuna Companies total compensation package for employees.</div></div>

AI Solutions Engineer

Occam Solutions

<div><p>Primary Responsibility</p><p></p><p><br>
The <b>DevSecOps Engineer</b> shall serve as the lead technical engineer responsible for designing, implementing, securing, automating, and sustaining the cloud infrastructure supporting the Office of Naval Research (ONR) Data &amp; Analytics environment. The DevSecOps Engineer shall lead the implementation and execution of the technical requirements identified in <b>PWS Section 4.5 &ndash; Technical Infrastructure and Platform Support</b>, including infrastructure automation, Continuous Integration/Continuous Deployment (CI/CD), cloud security, container orchestration, Infrastructure-as-Code (IaC), and operational sustainment of the FedRAMP High and DoD Impact Level 5 (IL5) cloud environment.</p><p></p><p><br>
The DevSecOps Engineer shall architect and maintain secure cloud infrastructure, automate deployment pipelines, support AI/ML platform integration, implement cloud-native security controls, monitor system health and security events, and ensure compliance with DoD cybersecurity requirements. This position will work closely with software developers, data engineers, cloud architects, cybersecurity personnel, and Government stakeholders to deliver resilient, scalable, and secure cloud services.</p><p></p><p><br>
Duties and Responsibilities</p>
<p>
The DevSecOps Engineer shall:</p>
<ul>
<li>Design, deploy, automate, and maintain secure cloud infrastructure supporting mission applications and analytics platforms.</li>
<li>Develop, implement, and manage automated CI/CD pipelines using tools such as Jenkins, GitLab CI/CD, or equivalent technologies.</li>
<li>Build and maintain Infrastructure-as-Code (IaC) solutions utilizing Terraform, Ansible, or similar automation frameworks.</li>
<li>Implement and manage containerized application environments using Docker, Kubernetes, or comparable orchestration platforms.</li>
<li>Configure, monitor, and optimize cloud-native security services including Web Application Firewalls (WAF), Intrusion Detection/Prevention Systems (IDS/IPS), endpoint protection, and Security Information and Event Management (SIEM) platforms.</li>
<li>Analyze security logs, audit events, vulnerability reports, and SIEM alerts to identify threats, recommend mitigation strategies, and support incident response activities.</li>
<li>Support continuous Authority to Operate (ATO) compliance through configuration management, security patching, vulnerability remediation, and security documentation.</li>
<li>Implement secure API management, identity and access management (IAM), secrets management, encryption, and least-privilege access controls.</li>
<li>Develop automated monitoring, logging, alerting, and operational dashboards to improve system reliability and performance.</li>
<li>Support deployment and operationalization of AI/ML platforms and services, including cloud-native machine learning environments.</li>
<li>Collaborate with software developers, data engineers, and cloud architects to integrate security throughout the software development lifecycle (SDLC).</li>
<li>Ensure cloud infrastructure complies with DoD cybersecurity policies, FedRAMP High requirements, DoD IL5 controls, and applicable security frameworks.</li>
<li>Support system scalability, resilience, disaster recovery, and operational continuity.</li>
<li>Document system architectures, deployment procedures, security configurations, and operational processes.</li></ul><br>
<p></p>
<p>
Minimum Qualifications</p>
<p>
The DevSecOps Engineer shall meet the requirements for the <b>&quot;DevSecOps Engineer &ndash; Intermediate&quot;</b> labor category as defined in the <b>CHESS ITES-3S</b> contract vehicle and possess the following additional qualifications:</p>
<ul>
<li>Seven (7) years of combined experience in DevSecOps, DevOps, SecOps, or MLOps engineering and development.</li>
<li>Five (5) years of hands-on experience designing, securing, implementing, and maintaining cloud environments, preferably within <b>AWS GovCloud</b>, <b>Azure Government</b>, or similarly regulated cloud environments.</li>
<li>Demonstrated experience supporting cloud environments operating under <b>FedRAMP High</b>, <b>DoD Impact Level 5 (IL5)</b>, or comparable federal security requirements.</li>
<li>Verifiable experience on at least two (2) projects designing, implementing, and managing Continuous Integration/Continuous Deployment (CI/CD) pipelines using Jenkins, GitLab CI/CD, Azure DevOps, GitHub Actions, or equivalent technologies.</li>
<li>Demonstrated expertise implementing and managing containerization and orchestration technologies, including Docker, Kubernetes, OpenShift, or similar platforms.</li>
<li>Hands-on experience implementing Infrastructure-as-Code (IaC) using Terraform, Ansible, CloudFormation, or comparable automation tools.</li>
<li>Experience configuring and administering cloud-native security capabilities including Web Application Firewalls (WAF), Intrusion Detection/Prevention Systems (IDS/IPS), Security Information and Event Management (SIEM), vulnerability management, and cloud security monitoring solutions.</li>
<li>Verifiable experience analyzing security logs, SIEM data, audit records, and threat intelligence to identify vulnerabilities, investigate security events, and implement corrective actions.</li>
<li>Experience implementing secure Identity and Access Management (IAM), encryption, secrets management, and Zero Trust security principles.</li>
<li>Experience supporting automated monitoring, logging, system performance optimization, and operational sustainment of enterprise cloud platforms.</li>
<li>Strong understanding of DevSecOps best practices, secure software development lifecycle (SSDLC), and cloud security architectures.</li><br>
</ul>
<p>Qualifications</p>
<ul>
<li>Active Secret security clearance (required).</li>
<li>Current DoD 8140 (or legacy DoD 8570) cybersecurity certification applicable to privileged access functions (e.g., Security+, CySA+, CASP+, CISSP, CCSP).</li>
<li>AWS Certified DevOps Engineer &ndash; Professional, AWS Security Specialty, Azure DevOps Engineer Expert, Certified Kubernetes Administrator (CKA), or comparable cloud certifications.</li>
<li>Experience supporting AI/ML environments, including AWS SageMaker, Azure Machine Learning, or similar platforms.</li>
<li>Experience with streaming data technologies such as Apache Kafka, AWS Kinesis, or equivalent event-driven architectures.</li>
<li>Familiarity with NIST RMF, DISA STIGs, FedRAMP, Zero Trust Architecture, and DoD cybersecurity compliance requirements.</li></ul></div>

DevSecOps Engineer

Valeo

<div>
 <strong>
  Responsibilities
  <br/>
  <br/>
 </strong>
 <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.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Qualifications
  <br/>
  <br/>
 </strong>
 <strong>
  <strong>
   Education &amp; Experience
   <br/>
   <br/>
  </strong>
 </strong>
 <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.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  <strong>
   Technical Requirements
   <br/>
   <br/>
  </strong>
 </strong>
 <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.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  <strong>
   Soft Skills &amp; Mindset
   <br/>
   <br/>
  </strong>
 </strong>
 <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

KeyBank

<div><p><b>Location:</b></p>
4910 Tiedeman Road, Brooklyn Ohio<p></p><p><b>
Department:</b> Contact Center Technology<br>
<b>Experience:</b> 4+ years</p><p></p><h3 class="jobSectionHeader"><b>
About the Role</b></h3><p>
KeyBank is seeking a <b>Lead AI Engineer</b> to design, build, and modernize AI-powered conversational experiences, IVR platforms, and Voice Bot solutions within the Contact Center Technology organization. This role serves as a senior hands-on engineer responsible for architecting, developing, and delivering AI-driven solutions that enhance customer self-service and agent experiences.</p><p>
Unlike a traditional technical lead role, this position is deeply focused on <b>hands-on AI engineering and solution delivery</b>. The Lead AI Engineer will spend the majority of their time designing, building, coding, integrating, and optimizing AI-powered applications while providing technical guidance across initiatives.</p><p>
The Lead AI Engineer partners closely with product, platform, voice, and operations teams to deliver secure, scalable, and highly reliable conversational AI solutions on Google Cloud Platform (GCP). This is a senior individual contributor role with delivery accountability, but no people management responsibility.</p><p></p><h3 class="jobSectionHeader"><b>
Key Responsibilities</b></h3><ul><li>
Design and develop AI-powered IVR and voice bot solutions leveraging modern conversational AI frameworks.</li><li>
Lead the technical architecture, engineering design, and implementation of AI-driven customer experience initiatives.</li><li>
Build and develop Node.js / TypeScript microservices aligned to cloud-native and low-latency voice requirements.</li><li>
Own end-to-end delivery of complex AI features, from concept and design through deployment and production support.</li><li>
Apply agentic AI patterns utilizing Gemini, LangGraph, LangChain, and emerging AI frameworks to enhance conversational experiences.</li><li>
Develop, test, evaluate, and optimize prompts, workflows, and AI orchestration strategies.</li><li>
Collaborate across the contact center technology ecosystem to support call routing, self-service, and agent handoff scenarios.</li><li>
Provide technical mentorship and code review support while contributing directly to development efforts.</li><li>
Establish engineering best practices for AI solution development, testing, deployment, and observability.</li><li>
Apply SRE principles to ensure resiliency, scalability, monitoring, and production readiness.</li><li>
Ensure solutions comply with security and regulatory requirements (PII / PCI).</li></ul><p></p><h3 class="jobSectionHeader"><b>
Required Skills &amp; Qualifications</b></h3><ul><li>
4+ years of software engineering experience, including 2+ years as a <b>Lead AI Engineer, Lead Engineer, Principal Engineer, or comparable senior technical contributor role</b>.</li><li>
Strong hands-on experience building and deploying AI-powered applications and services.</li><li>
Strong, hands-on experience with Node.js / TypeScript.</li><li>
Proven experience designing and delivering cloud-native solutions on GCP.</li><li>
Experience implementing and integrating LLMs, conversational AI platforms, and agentic AI frameworks.</li><li>
Solid understanding of microservices architecture, APIs, and distributed systems.</li><li>
Hands-on Kubernetes experience, including GKE cluster setup and platform operations.</li><li>
Experience with IVR, voice bots, conversational AI, or contact center technologies.</li><li>
Strong collaboration skills across engineering, product, and operations teams.</li><li>
Excellent technical judgment, communication, and problem-solving skills.</li></ul><p></p><h3 class="jobSectionHeader"><b>
Preferred Qualifications</b></h3><ul><li>
Experience with conversational AI and agentic frameworks (Gemini, LangGraph, LangChain).</li><li>
Experience developing AI agents, orchestration workflows, and multi-agent solutions.</li><li>
Knowledge of voice flows, call routing, containment, and agent escalation.</li><li>
Experience working in regulated or financial services environments.</li><li>
Familiarity with CI/CD pipelines, containerization, and Infrastructure as Code.</li><li>
Experience working in Agile delivery models at enterprise scale.</li><li>
Demonstrated experience with Agentic &quot;Vibe Coding&quot; &mdash; rapid prototyping and iterative development using AI-assisted coding tools, prompts, and agent-driven workflows.</li></ul><p></p><p><i>
This position is NOT eligible for employment visa sponsorship for non-U.S. citizens.</i></p><p></p><p>
COMPENSATION AND BENEFITS</p>
This position is eligible to earn a base salary in the range of $96,000.00 - $181,000.00 annually. Placement within the pay range may differ based upon various factors, including but not limited to skills, experience and geographic location. Compensation for this role also includes eligibility for incentive compensation which may include production, commission, and/or discretionary incentives.<p></p><p>
Please click here for a list of benefits for which this position is eligible.</p><p></p><p>
Key has implemented an approach to employee workspaces which prioritizes in-office presence, while providing flexible options in circumstances where roles can be performed effectively in a mobile environment.</p><p></p>
Job Posting Expiration Date: 09/11/2026 KeyCorp is an Equal Opportunity Employer committed to sustaining an inclusive culture. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, genetic information, pregnancy, disability, veteran status or any other characteristic protected by law.<p></p><p>
Qualified individuals with disabilities or disabled veterans who are unable or limited in their ability to apply on this site may request reasonable accommodations by emailing HR_Compliance@keybank.com.</p><br>
<p></p>
#LI-Remote</div>

Lead AI Engineer

Kentan Staffing Solutions

<div><div><h1 class="jobSectionHeader"><b>Founding Software Engineer
</b></h1><p><b>Location: </b>New York, NY (Onsite)
</p><p><b>Employment Type: </b>Full-Time | Direct Hire
</p><p><b>Compensation: </b>$200,000&ndash;$220,000 Base Salary + Equity (Competitive Benefits)
</p><p><b>Interview Process: </b>3 Interviews
</p><h2 class="jobSectionHeader"><b>Position Overview
</b></h2><p>Our client, a rapidly growing AI startup revolutionizing the insurance industry, is seeking a <b>Founding Software Engineer </b>to join its core Engineering team. This is a unique opportunity to become an early engineering hire, helping build the platform that powers enterprise AI agents used by some of the world's largest insurance carriers.
</p><p>This role is ideal for an experienced software engineer who thrives in early-stage startup environments and enjoys solving complex distributed systems challenges. You'll play a foundational role in designing scalable infrastructure, developing AI-powered platforms, and building the engineering systems that enable rapid product innovation.
</p><p>The ideal candidate is highly autonomous, technically exceptional, and excited by the opportunity to own critical systems from architecture through production. Culture fit is extremely important&mdash;the team values individuals who are personable, collaborative, scrappy, and capable of moving quickly with minimal direction.
</p><h2 class="jobSectionHeader"><b>Key Responsibilities
</b></h2><ul><li>Design, build, and maintain the core platform powering AI agents across the organization.
</li><li>Develop highly scalable backend services and infrastructure using TypeScript, SQL, and modern cloud technologies.
</li><li>Build and optimize agent orchestration, execution platforms, and developer tooling.
</li><li>Design resilient distributed systems with fault tolerance, observability, retries, and graceful degradation.
</li><li>Develop internal platforms that improve engineering productivity, CI/CD pipelines, and automation workflows.
</li><li>Partner closely with Forward Deployed Engineers to rapidly transform customer feedback into production-ready features.
</li><li>Write technical specifications, review architecture, and deliver high-quality production code.
</li><li>Improve platform reliability, performance, security, and scalability while supporting rapid company growth.
</li><li>Contribute to engineering best practices, code reviews, and long-term platform strategy.
</li></ul><h2 class="jobSectionHeader"><b>Required Qualifications
</b></h2><ul><li>4+ years of experience building production software in a Software Engineer, Backend Engineer, or Platform Engineer role.
</li><li>Strong programming experience with <b>TypeScript </b>and <b>SQL </b>.
</li><li>Experience designing and building scalable backend systems and distributed applications.
</li><li>Strong understanding of system architecture, APIs, databases, and cloud infrastructure.
</li><li>Experience building highly reliable systems with monitoring, observability, retries, circuit breakers, and fault tolerance.
</li><li>Experience working in regulated or security-conscious environments with strong auditing and compliance requirements.
</li><li>Self-starter with exceptional problem-solving skills and the ability to work independently in a fast-paced startup environment.
</li><li>Must be located in or willing to relocate to New York City.
</li></ul><h2 class="jobSectionHeader"><b>Preferred Qualifications
</b></h2><ul><li>Experience building AI, LLM, or agent-based platforms.
</li><li>Experience with developer platforms, CI/CD automation, and internal engineering tooling.
</li><li>Background building high-performance distributed systems or infrastructure platforms.
</li><li>Experience working in high-growth startups or founding engineering teams.
</li><li>Familiarity with cloud-native architecture, containerization, and modern DevOps practices.
</li></ul><h2 class="jobSectionHeader"><b>What We're Looking For
</b></h2><ul><li>Highly autonomous engineer who takes full ownership from concept to production.
</li><li>Scrappy, resourceful, and thrives in ambiguous, fast-moving environments.
</li><li>Strong technical leader with a builder's mindset and passion for creating scalable systems.
</li><li>Collaborative team player who enjoys working closely with product, engineering, and customer-facing teams.
</li><li>Passionate about leveraging AI to solve complex, real-world business challenges.
</li></ul><p>This is an exceptional opportunity to join a venture-backed AI startup at an early stage, working alongside an elite engineering team to build the next generation of autonomous AI systems while making a significant impact on both the product and the future direction of the company.</p></div></div>

Founding Software Engineer

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